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CCD or CMOS Image sensor for photography
... • Theanalog CCD sensor which converts photons to electrons • The digital CMOS image sensor (CIS) which converts photon intensity to voltage [5][6][7][8] ...
... Each of this MOS diode is called a pixel. When a photon falls on the pixel electrons are generated in the individual device [5][6][7][8]. The generation of electrons is directly proportional to the intensity at each pixel. ...
... The image artifact in CCD includes smearing and charge transfer inefficiency, FPN (Fixed Pattern Noise) and PLS (Proximity Laser Scanner) are demonstrated in CMOS. High sensor complexity can be observed in CMOS when compared CCD, but whereas, system complexity is observed more in CCD when compared CMOS.Research and development cost high for CMOS when compared to CCD [4][5][6][7][8]. ...
Image sensors are used in all digital cameras, mobile phones and all other devices where images are to be captured. The most common parameter used by consumers to compare the different cameras is the pixel array size which is usually given in Mega pixels. The image quality is better with a higher megapixel count. Another parameter to distinguish between the different cameras is the type of imaging technology used like CMOS (Complementary metal oxide semiconductor) or CCD (Charge coupled devices). In this review we will present the working principles of an image sensor and conversion of light to electrical signals and subsequently to an image. The functional differences between the CCD and CMOS sensors will also be presented.
... Working principle: The camera is a digital lens imagery system that works by collecting and translating the image of an object into electrons on a pixel image sensor. Later, the camera capacitors convert electrons into voltages, which are later converted into an electronic digital signal [155]. Two imaging sensors, the charging coupling device (CCD) and the complementary metal oxide semiconductor device (CMOS-D), are typically used in real-time applications. ...
... Brief comparisons Working principle: The camera is a digital lens imagery system that works by collecting and translating the image of an object into electrons on a pixel image sensor. Later, the camera capacitors convert electrons into voltages, which are later converted into an electronic digital signal [155]. Two imaging sensors, the charging coupling device (CCD) and the complementary metal oxide semiconductor device (CMOS-D), are typically used in real-time applications. ...
... Two imaging sensors, the charging coupling device (CCD) and the complementary metal oxide semiconductor device (CMOS-D), are typically used in real-time applications. Brief comparisons between the CCD and CMOS-D can be found in [155,156]. CCD cameras deliver excellent low-noise performance but are expensive and, as an alternative, the CMOS-D has been developed to reduce production costs and power consumption. Because of this advantage, the CMOS-D is widely preferred for automotive applications in the related industry. ...
Perception is a vital part of driving. Every year, the loss in visibility due to snow, fog, and rain causes serious accidents worldwide. Therefore, it is important to be aware of the impact of weather conditions on perception performance while driving on highways and urban traffic in all weather conditions. The goal of this paper is to provide a survey of sensing technologies used to detect the surrounding environment and obstacles during driving maneuvers in different weather conditions. Firstly, some important historical milestones are presented. Secondly, the state-of-the-art automated driving applications (adaptive cruise control, pedestrian collision avoidance, etc.) are introduced with a focus on all-weather activity. Thirdly, the most involved sensor technologies (radar, lidar, ultrasonic, camera, and far-infrared) employed by automated driving applications are studied. Furthermore, the difference between the current and expected states of performance is determined by the use of spider charts. As a result, a fusion perspective is proposed that can fill gaps and increase the robustness of the perception system.
... The electronic device used to capture a scene is known as an imaging sensor. CCD (charge coupled device) and CMOS (complementary metal oxide semiconductor) are the most commonly utilized technologies in image sensors (Mehta et al., 2015;Ardeshirpour et al., 2006) [60,8] . Recent technological advancements in cameras indicate that manufacturers such as IMEC (India-Middle East-Europe Economic Corridor), a world leader in nanoelectronics, are working to integrate TDI (time delay integration) technology with image sensor characteristics within a single device. ...
... The electronic device used to capture a scene is known as an imaging sensor. CCD (charge coupled device) and CMOS (complementary metal oxide semiconductor) are the most commonly utilized technologies in image sensors (Mehta et al., 2015;Ardeshirpour et al., 2006) [60,8] . Recent technological advancements in cameras indicate that manufacturers such as IMEC (India-Middle East-Europe Economic Corridor), a world leader in nanoelectronics, are working to integrate TDI (time delay integration) technology with image sensor characteristics within a single device. ...
The advent of high-throughput phenotyping (HTP) technologies has revolutionized crop improvement by enabling rapid, non-destructive measurement of multiple plant traits. These advanced methods facilitate the efficient collection of phenotypic data, bridging the gap between traditional phenotyping and modern genomics. These technologies allow for the comprehensive analysis of complex traits, such as growth, yield and stress adaptations, under diverse environmental conditions. By integrating imaging techniques like near infrared, far infrared, thermal and hyper spectral imaging techniques with machine learning algorithms, high throughput phenotyping enhances the accuracy and efficiency of plant characters measurements. This dynamic approach enables the discovery of novel traits and accelerates breeding programs by providing deeper insights into genotype-phenotype relationships. Additionally, these technologies supports the continuous monitoring of plant development, stress responses and adaptive mechanisms, off
... The astronomy, photography, medical, scanners and many more used the CCD as the sensor as it provides high resolution photos, low noise, and also low power. CCD is applied in telescope, cameras, scanners, X-ray computed tomography (CT), MRI scanner and many more [10,11,12,13,14]. Furthermore, CCD sensor is also very competent in detecting transparency of objects according to the experiment conducted by previous researchers [11,12,13]. ...
... CCD is applied in telescope, cameras, scanners, X-ray computed tomography (CT), MRI scanner and many more [10,11,12,13,14]. Furthermore, CCD sensor is also very competent in detecting transparency of objects according to the experiment conducted by previous researchers [11,12,13]. ...
Ruby is one of the most popular and high-value gemstones that always attract the gemologist and jeweler in the diamond market. The wide use of ruby in various industries makes the grading of this gems more complicated due to a lot of synthetic and imitation rubies are made. The current grading techniques are mostly depending on the human visual assessment which prone to errors. This paper proposes a system that helps in grading the clarity characteristic of the ruby in non-invasive manner. The system includes a charge-coupled devices (CCD) and laser that is designed in the most suitable and effective way to conduct inspection on the light intensity of the ruby which will then determine the clarity of the ruby. CCD linear sensor is widely known as the reliable sensor especially when use in the optical system. The CCD linear sensor capture the light intensity from the ruby and convert it into the voltage value. The result shows a value of 1.7918 V obtained from the CCD linear sensor when ruby is placed in the system. This concludes that the CCD system can detect even slightest changes in the light intensity that can pass through the ruby and falls on the CCD linear sensor. The system is proven to be a reliable and effective system with 80% accuracy.
... Today, CCDs have almost been replaced by CMOS sensors, because CMOS technology offers substantial advantages, such as low voltage supply, low power consumption, and longer battery life, as well as integration, thus allowing for the manufacture of single-chip miniaturized digital cameras or high-speed imaging [58]. CCD sensors offer some advantages over CMOS sensors; they tend to suffer from less sources of noise [59] and allow high-quality photographs [60]. Initially, CMOS sensors had poor pixel performance compared to CCD imagers, but they have evolved to achieve high-quality image performance, which is now comparable to that of CCDs [61]. ...
... Due to their low cost and small size, smartphones mostly incorporate CMOS image sensors [60]. In recent years, smartphone image sensors have been widely used to detect UV radiation [127]. ...
Today, there are many attempts to introduce the Internet of Things (IoT) in high-voltage systems, where partial discharges are a focus of concern since they degrade the insulation. The idea is to detect such discharges at a very early stage so that corrective actions can be taken before major damage is produced. Electronic image sensors are traditionally based on charge-coupled devices (CCDs) and, next, on complementary metal oxide semiconductor (CMOS) devices. This paper performs a review and analysis of state-of-the-art image sensors for detecting, locating, and quantifying partial discharges in insulation systems and, in particular, corona discharges since it is an area with an important potential for expansion due to the important consequences of discharges and the complexity of their detection. The paper also discusses the recent progress, as well as the research needs and the challenges to be faced, in applying image sensors in this area. Although many of the cited research works focused on high-voltage applications, partial discharges can also occur in medium- and low-voltage applications. Thus, the potential applications that could potentially benefit from the introduction of image sensors to detect electrical discharges include power substations, buried power cables, overhead power lines, and automotive applications, among others.
... An optical transducer converts light or photons into an electrical signal [1,2]. These include linear and area or matrix sensors, regardless of the working principle, e.g., Charge Coupled Device (CCD) and Complementary Metal Oxide Semiconductor (CMOS) [1,3]. Individual sensors and fully assembled products and devices integrating the mentioned image or light sensor are considered. ...
... Table 1 shows the results of an example of a test. 3 Signal to Noise ratio (SNR). Figure 9 presents the results of the spectral analysis applied to the quantum efficiency calculation. ...
This paper presents the development of a hardware/software system for the characterization of the electronic response of optical (camera) sensors such as matrix and linear color and monochrome Charge Coupled Device (CCD) or Complementary Metal Oxide Semiconductor (CMOS). The electronic response of a sensor is required for inspection purposes. It also allows the design and calibration of the integrating device to achieve the desired performance. The proposed instrument equipment fulfills the most recent European Machine Vision Association (EMVA) 1288 standard ver. 3.1: the spatial non uniformity of the illumination ΔE must be under 3%, and the sensor must achieve an f-number of 8.0 concerning the light source. The following main innovations have achieved this: an Ulbricht sphere providing a uniform light distribution (irradiation) of 99.54%; an innovative illuminator with proper positioning of color Light Emitting Diodes (LEDs) and control electronics; and a flexible C# program to analyze the sensor parameters, namely Quantum Efficiency, Overall System Gain, Temporal Dark Noise, Dark Signal Non Uniformity (DSNU1288), Photo Response Non-Uniformity (PRNU1288), Maximum achievable Signal to Noise Ratio (SNRmax), Absolute sensitivity threshold, Saturation Capacity, Dynamic Range, and Dark Current. This new instrument has allowed a camera manufacturer to design, integrate, and inspect numerous devices and camera models (Necta, Celera, and Aria).
... In the image capture section, charged coupled device (CCD) (Mehta et al., 2015) has played an important role for its high sensitivity and low signal noise over the last few decades. However, owing to improvement of the semiconductor process in recent years, the drawbacks of complementary metal oxide semiconductor (CMOS) (Chen & Perng, 2005;Mehta et al., 2015), involving its low sensitivity and noise are overcome. ...
... In the image capture section, charged coupled device (CCD) (Mehta et al., 2015) has played an important role for its high sensitivity and low signal noise over the last few decades. However, owing to improvement of the semiconductor process in recent years, the drawbacks of complementary metal oxide semiconductor (CMOS) (Chen & Perng, 2005;Mehta et al., 2015), involving its low sensitivity and noise are overcome. Its performance can mostly keep up with that of CCD. ...
Traditional inspection systems with a single light source are not efficient at detecting a few particular defects with a single inspection. Unlike before, the multi-light source inspection environment allows us to extract more different defects in a piece of work, depending on what we are working on with varying sources of light. We proposed the formulation of the multi-lights source lighting strategy to improve the inspection capability of Automated Optical Inspection (AOI). The process of developing this study not only utilizes the ubiquitous image processing to extract defects but also imports the design of generalized defect sample and reinforcement learning, dealing with diverse defects under in-depth inspection by cascading both light and camera parameters. As a result, the AOI system emphasized that the inspection parameters can be intelligently adjusted to appropriate values based on various defects, maximizing the detection of diverse defects. From the perspective of intelligent AOI results, there are two outstanding outcomes for a multi-light source lighting strategy. One is an efficient learning process, which facilitates us to obtain the strategy needed in 40 to 50 min, depending on the reward function designed. The other is an advanced inspection function that can extract 37% more defects than conventional methods.
... Complementary Metal Oxide Semiconductor Devices (CMOS) similarly operates under the same principle as the CDDs but their accumulated charge is amplified at each cell unit/pixel by multiple chip amplifiers, respectively [62]. Advantages of CMOS over CCD include; low power consumption, being inexpensive and easy to manufacture [63]. On the other hand, CCDs merits have; fast speeds, high dynamic ranges, greater light sensitivity and produce high-quality low noise images [63]. ...
... Advantages of CMOS over CCD include; low power consumption, being inexpensive and easy to manufacture [63]. On the other hand, CCDs merits have; fast speeds, high dynamic ranges, greater light sensitivity and produce high-quality low noise images [63]. Factors such as camera size and noise [64,65] could also be a device preference and selection criteria. ...
Numerous instruments such as ionization chambers, hand-held and pocket dosimeters of various types, film badges, thermoluminescent dosimeters (TLDs) and optically stimulated luminescence dosimeters (OSLDs) are used to measure and monitor radiation in medical applications. Of recent, photonic devices have also been adopted. This article evaluates recent research and advancements in the applications of photonic devices in medical radiation detection primarily focusing on four types; photodiodes – including light-emitting diodes (LEDs), phototransistors—including metal oxide semiconductor field effect transistors (MOSFETs), photovoltaic sensors/solar cells, and charge coupled devices/charge metal oxide semiconductors (CCD/CMOS) cameras. A comprehensive analysis of the operating principles and recent technologies of these devices is performed. Further, critical evaluation and comparison of their benefits and limitations as dosimeters is done based on the available studies. Common factors barring photonic devices from being used as radiation detectors are also discussed; with suggestions on possible solutions to overcome these barriers. Finally, the potentials of these devices and the challenges of realizing their applications as quintessential dosimeters are highlighted for future research and improvements.
... Master files received with scanners are generally saved in TIFF format and can reach 700 Mb or more, which requires superior storage capacities. However, scanners with CCD sensors often produce images of better quality (especially regarding the sharpness and colour reproduction) and resolution (Waltham 2013, Mehta et al. 2015, Tejas et al. 2022 compared to the commonly used photocameras with CMOS sensors. Photo stations are usually less expensive to construct, modular and better suited to various working spaces. ...
The digitisation workflow currently applied at the Herbarium of the State Museum of Natural History of the National Academy of Sciences of Ukraine (LWS) differs from other similar by cascade ('object-to-data-to-image') multilevel organisation. Its application is predicted by the need to preselect specimens by taxon and region, as well as by batched digitisation, which occurs with significant interruptions. Focusing on certain taxonomic groups from specific regions allows us to digitise specimens that could be more valuable for early scientific processing. At the same time, the herbarium benefits from such a digitisation model by revising the existing collection classification and keeping the initial ID system. The presented digitisation workflow can be easily reproduced in any herbarium with a limited budget. The purpose of this paper is to provide detailed description and schemas of the principal digitisation stages applied at the LWS Herbarium and to briefly discuss the steps crucial for a successful result. Provided information should help to maintain the digitisation and choose appropriate equipment and materials. We can conclude that, despite its general complexity, the described workflow demonstrated itself as viable and relevant due to its robust design and focus on data quality. Despite a focus on specialists' involvement, it maintains flexibility that allows combining volunteers and, if needed, outsourced efforts. Moreover, its modularity promotes independence of principal digitisation stages and allows long interruptions between the digitisation batches.
... The researchers have tried numerous ways to design image sensors. Charge coupled devices (CCD) are one of the early-stage sensors [26], [27], invented back in 1970. These sensors did not continue because they were very slow, required several clock-cycles for completing a readout, and the situation deteriorates with the increasing number of pixels [28]. ...
Digital pixel sensor (DPS) has evolved as a pivotal component in modern imaging systems and has the potential to revolutionize various fields such as medical imaging, astronomy, surveillance, IoT devices, etc. Compared to analog pixel sensors, the DPS offers high speed and good image quality. However, the introduced intrinsic complexity within each pixel, primarily attributed to the accommodation of the ADC circuit, engenders a substantial increase in the pixel pitch. Unfortunately, such a pronounced escalation in pixel pitch drastically undermines the feasibility of achieving high-density integration, which is an obstacle that significantly narrows down the field of potential applications. Nonetheless, designing compact conversion circuits along with strategic integration of 3D architectural paradigms can be a potential remedy to the prevailing situation. This review article presents a comprehensive overview of the vast area of DPS technology. The operating principles, advantages, and challenges of different types of DPS circuits have been analyzed. We categorize the schemes into several categories based on ADC operation. A comparative study based on different performance metrics has also been showcased for a well-rounded understanding.
... The researchers have tried numerous ways to design image sensors. Charge coupled devices (CCD) are one of the early-stage sensors [26], [27], invented back in 1970. These sensors did not continue because they were very slow, required several clock-cycles for completing a readout, and the situation deteriorates with the increasing number of pixels [28]. ...
Digital pixel sensor (DPS) has evolved as a pivotal component in modern imaging systems and has the potential to revolutionize various fields such as medical imaging, astronomy, surveillance, IoT devices, etc. Compared to analog pixel sensors, the DPS offers high speed and good image quality. However, the introduced intrinsic complexity within each pixel, primarily attributed to the accommodation of the ADC circuit, engenders a substantial increase in the pixel pitch. Unfortunately, such a pronounced escalation in pixel pitch drastically undermines the feasibility of achieving high-density integration, which is an obstacle that significantly narrows down the field of potential applications. Nonetheless, designing compact conversion circuits along with strategic integration of 3D architectural paradigms can be a potential remedy to the prevailing situation. This review article presents a comprehensive overview of the vast area of DPS technology. The operating principles, advantages, and challenges of different types of DPS circuits have been analyzed. We categorize the schemes into several categories based on ADC operation. A comparative study based on different performance metrics has also been showcased for a well-rounded understanding.
... 2. High-Resolution Camera Sensor: The introduction of high-resolution compact sensor has led to substantial improvements in the clarity and detail of images captured during solder joint inspection [21,22,23,24]. This advancement enhances the ability to detect even the smallest defects that could critically affect the reliability of the joints. ...
This paper reviews the entire vision inspection cycle, encompassing image acquisition, image enhancement, Region of Interest (ROI) localization and segmentation, features extraction followed by defect detection and classification.
The aim of the study is to identify potential image processing time saving.
The investigation innovatively suggests that optimizing image enhancement and ROI localization processing time could significantly accelerate the overall inspection cycle time without negatively impacting inspection accuracy.
In Automated Optical Inspection (AOI) machine, camera sensor is mounted on precision X-Y gantries. To acquire images for inspection, the gantries will accurately move the camera to the predetermined coordinate position as stipulated in the inspection program. The vision camera will then capture the desired image using specified Field of View (FOV). Only ROI which is the solder joint position will be extracted out from the FOV image for processing.
Meanwhile, the designated solder joint positions (i.e. solder pad coordinates) for all electronic components mounted on the PCB are priory known extracted from the PCB fabrication file. These coordinates can be used directly for ROI localization without employing any algorithm, and yet accuracy is not compromised.
Meanwhile, through leveraging the state-of-art vision hardware, namely high-resolution camera and adaptive lighting system, quality images can be acquired and used directly without the need for any enhancement.
Comparison analysis based on industrial PCB having 1000 electronics components (with 3000 solder joints of size 140x70 pixels per joint), the processing time utilizing NVIDIA GeForce RTX 2060 series Graphic Processing Unit (GPU) and Template Matching Algorithm for ROI localization needs 2 seconds. whereas when using Multiscale Morphology Algorithm for image enhancement, time required is approximately 3 seconds.
Benchmarking of a typical production line with bottleneck cycle time of 25 seconds, indicating that the proposed methodology effectively addresses the challenges faced while implementing real-time machine vision inspection system in the industry, aligned with Industrial 4.0 Smart Manufacturing initiatives.
... Images were captured using a Charged Coupled Device (CCD) camera at a resolution of 640 × 480. In [29], the selection of a CCD camera over a Complementary Metal Oxide Semiconductor (CMOS) is motivated. Figure 4 illustrates the captured images for the varying conditions. ...
This article presents a computer vision-based approach to switching electric locomotive power supplies as the vehicle approaches a railway neutral section. Neutral sections are defined as a phase break in which the objective is to separate two single-phase traction supplies on an overhead railway supply line. This separation prevents flashovers due to high voltages caused by the locomotives shorting both electrical phases. The typical system of switching traction supplies automatically employs the use of electro-mechanical relays and induction magnets. In this paper, an image classification approach is proposed to replace the conventional electro-mechanical system with two unique visual markers that represent the ‘Open’ and ‘Close’ signals to initiate the transition. When the computer vision model detects either marker, the vacuum circuit breakers inside the electrical locomotive will be triggered to their respective positions depending on the identified image. A Histogram of Oriented Gradient technique was implemented for feature extraction during the training phase and a Linear Support Vector Machine algorithm was trained for the target image classification. For the task of image segmentation, the Circular Hough Transform shape detection algorithm was employed to locate the markers in the captured images and provided cartesian plane coordinates for segmenting the Object of Interest. A signal marker classification accuracy of 94% with 75 objects per second was achieved using a Linear Support Vector Machine during the experimental testing phase.
... For the acquisition of the surface defect images of the aluminum profiles, We use a Basler ace acA1300-30gm camera from BASLER in Aachen, Germany, as illustrated in Figure 7. The Basler ace acA1300-30gm utilizes the Sony ICX445 CCD sensor, which is a commonly used imaging sensor technology in digital cameras and machine vision systems, providing high-quality images [34]. The CCD sensor is composed of an array of tiny photosensitive units (pixels). ...
To address the various challenges in aluminum surface defect detection, such as multiscale intricacies, sensitivity to lighting variations, occlusion, and noise, this study proposes the AluDef-ClassNet model. Firstly, a Gaussian difference pyramid is utilized to capture multiscale image features. Secondly, a self-attention mechanism is introduced to enhance feature representation. Additionally, an improved residual network structure incorporating dilated convolutions is adopted to increase the receptive field, thereby enhancing the network’s ability to learn from extensive information. A small-scale dataset of high-quality aluminum surface defect images is acquired using a CCD camera. To better tackle the challenges in surface defect detection, advanced deep learning techniques and data augmentation strategies are employed. To address the difficulty of data labeling, a transfer learning approach based on fine-tuning is utilized, leveraging prior knowledge to enhance the efficiency and accuracy of model training. In dataset testing, our model achieved a classification accuracy of 97.6%, demonstrating significant advantages over other classification models.
... CMOS and CCD image sensor development began concurrently [75]. Due to the constraints of the process level at the time, CMOS resolution was low, there was a great deal of noise, light sensitivity was low [76], and the quality was poor; it also acheived little improvement. In contrast, CCD image sensors have dominated the market for two or three decades due to their broad effective light sensitivity area, uniform acquisition, low noise, and other advantages. ...
Identification technology based on biometrics is a branch of research that employs the unique individual traits of humans to authenticate identity, which is the most secure method of identification based on its exceptional high dependability and stability of human biometrics. Common biometric identifiers include fingerprints, irises, and facial sounds, among others. In the realm of biometric recognition, fingerprint recognition has gained success with its convenient operation and fast identif ication speed. Different fingerprint collecting techniques, which supply fingerprint information for fingerprint identification systems, have attracted a significant deal of interest in authentication technology regarding fingerprint identification systems. This work presents several fingerprint acquisition techniques, such as optical capacitive and ultrasonic, and analyzes acquisition types and structures. In addition, the pros and drawbacks of various sensor types, as well as the limits and benefits of optical, capacitive, and ultrasonic kinds, are discussed. It is the necessary stage for the application of the Internet of Things (IoT).
... Monaldi et al. (2016) expressed that CMOS sensor offers many advantages as compared to CCD sensors such as less thermal noise, higher resolution, and higher frame rates when capturing images. There are several vital characteristics to capture highquality images such as dark current noise, fill factor, quantum efficiency (QE), and charge transfer efficiency (CTE) (Mehta et al., 2015). Thus far, CCD image sensor has better performance than that CMOS with a higher fill factor (percentage of pixels sensitive to light), less affected dark current noise (depends on temperature), and higher charge transfer efficiency. ...
The identification of microalgae species is an important tool in scientific research and commercial application to prevent harmful algae blooms (HABs) and recognizing potential microalgae strains for the bioaccumulation of valuable bioactive ingredients. The aim of this study is to incorporate rapid, high-accuracy, reliable, low-cost, simple, and state-of-the-art identification methods. Thus, increasing the possibility for the development of potential recognition applications, that could identify toxic-producing and valuable microalgae strains. Recently, deep learning (DL) has brought the study of microalgae species identification to a much higher depth of efficiency and accuracy. In doing so, this review paper emphasizes the significance of microalgae identification, and various forms of machine learning algorithms for image classification, followed by image pre-processing techniques, feature extraction, and selection for further classification accuracy. Future prospects over the challenges and improvements of potential DL classification model development, application in microalgae recognition, and image capturing technologies are discussed accordingly.
... From the calculated n x − n y ≈ 5 × 10 −7 the relative angular phase shift ∆ xy ≈ 0.05 and the relative change in the light intensity sin 2 ( ∆ xy 2 ) ≈ 6.3 × 10 −4 (see Appendix A.1). Such a small change in the intensity is still well above the noise levels of commercial consumer-grade photosensors [39], allowing the use of cheap photosensors to build the photoelastic sensors. ...
The sense of touch is fundamental for a one-to-one mapping between the environment and a robot that physically interacts with the environment. Herein, we describe a tactile fingertip design that can robustly detect interaction forces given data collected from a camera. This design is based on the photoelastic effect observed in silicone matter. Under the force applied to the silicone rubber, owing to the stress-induced birefringence, the light propagating within the silicone rubber is subjected to the angular phase shift, where the latter is proportional to the increase in the image brightness in the camera frames. We present the calibration and test results of the photoelastic sensor design on a bench using a robot arm and with a certified industrial force torque sensor. We also discuss the applications of this sensor design and its potential relationship with human mechano-transduction receptors. We achieved a force sensing range of up to 8 N with a force resolution of around 0.5 N. The photoelastic tactile fingertip is suitable for robot grasping and might lead to further progress in robust tactile sensing.
... Modern space X-ray astronomy detection techniques have advanced significantly in the direction of low noise, low power, and huge scale. Because it outperforms conventional high-energy particle detectors in terms of both energy and spatial resolutions, the X-ray charge-coupled device (CCD) has a wide range of applications in the X-ray astronomy field [18]. CCD technology is also employed in X-ray Computed Tomography (CT). ...
Charge-Coupled Device (CCD) is a semiconductor chip with a light-sensitive sensor. The CCD has been used in many fields of engineering, including astronomy, medical sciences and processing. CCD is capable to detect light sources and convert this analogue signal into electrical signal. CCD is an integrated circuit that contains a large number of small photo elements with high sensitivity to light energy. The main focus of this research paper is on the review of CCD basic operating principle and construction, CCD characteristic, and the application of CCD in tomography system. The potential use of CCD in the gemological industry is also highlighted in this paper. Gemology is one of the important industries that considered profitable and crucial that deals with precious stones. This industry is in need of standardized grading valuation of gemstones as the current technique is prone to errors. An approach to the standardized grading technique is proposed where CCD tomography is used to detect and analyze the light distribution characteristic in ruby stones.KeywordsCharge-Coupled Device (CCD)GemologyLight distributionRubyTomography
... The 3D Histech Pannoramic 250 Flash III has an image capture rate of 130 frames per second [35] energy to convert the measured information into a digital signal. [34,50,51] Some vendors, for example, 3D Histech, have incorporated newer sCMOS sensors (first released to the public in 2009) into modern WSI device models. CCD, CMOS, and sCMOS sensors each present unique advantages and shortcomings. ...
Digital pathology (DP) has disrupted the practice of traditional pathology, including applications in education, research, and clinical practice. Contemporary whole slide imaging (WSI) devices include technological advances that help address some of the challenges facing modern pathology, such as increasing workloads with fewer subspecialized pathologists, expanding integrated delivery networks with global reach, and greater customization when working up cases for precision medicine. This review focuses on integral hardware components of 43 market available and soon-to-be released digital WSI devices utilized throughout the world. Components such as objective lens type and magnification, scanning camera, illumination, and slide capacity were evaluated with respect to scan time, throughput, accuracy of scanning, and image quality. This analysis of assorted modern WSI devices offers essential, valuable information for successfully selecting and implementing a digital WSI solution for any given pathology practice.
... A combination of visible and infrared (IR) cameras would effectively capture environment information, thereby resulting in a better analysis of different driving environments with different climatic conditions. Monocular cameras make use of image sensing components such as Charge-Coupled Devices (CCD) or the complementary metal-oxide-semiconductor (CMOS) [14]. The IR camera [15] sensing mechanism works for IR wavelengths ranging from 780nm to 1mm. ...
Over the last decade, the Advanced Driver Assistance System (ADAS) concept has evolved significantly. ADAS involves several technologies such as automotive electronics, vehicle-to-vehicle (V2V) vehicle-to-infrastructure (V2I) communication, RADAR, LIDAR, computer vision, and machine learning. Of these, computer vision and machine learning-based solutions have mainly been effective that have allowed real-time vehicle control, driver aided systems, etc. However, most of the existing works deal with the deployment of ADAS and autonomous driving functionality in countries with well-disciplined lane traffic. Nevertheless, these solutions and frameworks do not work in countries and cities with less-disciplined/chaotic traffic. This paper identifies the research gaps, reviews the state-of-the-art looking at the different functionalities of ADAS and its levels of autonomy. Importantly, it provides a detailed description of vision intelligence and computational intelligence for ADAS. In visual intelligence, the estimate of eye gaze and head position is detailed. Notably, the learning algorithms such as supervised, unsupervised, reinforcement learning and deep learning solutions for ADAS are considered and discussed. Significantly, this would enable developing a real-time recommendation system for system-assisted/autonomous vehicular environments with less-disciplined road traffic.
... Currently, CCD sensors are widely used in machine vision [64][65][66]. CMOS image sensors are still in their early stages and yet to mature [67,68]. The CMOS image sensors can get an image quality similar to that of CCD product and have made great breakthroughs in terms of power consumption and integration. ...
Machine vision significantly improves the efficiency, quality, and reliability of defect detection. In visual inspection, excellent optical illumination platforms and suitable image acquisition hardware are the prerequisites for obtaining high-quality images. Image processing and analysis are key technologies in obtaining defect information, while deep learning is significantly impacting the field of image analysis. In this study, a brief history and the state of the art in optical illumination, image acquisition, image processing, and image analysis in the field of visual inspection are systematically discussed. The latest developments in industrial defect detection based on machine vision are introduced. In the further development of the field of visual inspection, the application of deep learning will play an increasingly important role. Thus, a detailed description of the application of deep learning in defect classification, localization and segmentation follows the discussion of traditional defect detection algorithms. Finally, future prospects for the development of visual inspection technology are explored.
... With the development of CMOS detector in recent years, its performance has been comparable to that of traditional CCD detectors. Compared with CCD detector, CMOS detector also has the advantages of low cost, low power consumption, high frame rate, excellent anti-irradiation performance, and high integration, which make it widely used in the field of space remote sensing [1,2] . Different from the simultaneous exposure process of general detectors, the rolling shutter CMOS detectors adopt line-by-line exposure mode, which will inevitably introduce geometric distortion in the presence of image motion [3] . ...
... Technical features of recording optical signals with sensors of various types are considered in published sources [1]. Spectral characteristics of charge-coupled devices (ССD) and complementary metal-oxide semiconductors (CMOS) explain the need for separating devices in photosensitive matrices [2]. ...
Complexity of integrating color control systems into a workflow for obtaining digital half-tone images results in appearance of color rendering imperfections in photographic images as exposure conditions constantly vary in power and spectral composition of radiation. A wide range of corrective means in graphic editors does not ensure full elimination of color rendering imperfections in photographic images because of imperfect technical approaches to realization of the corrective effect.
The process of correcting color rendering imperfections is complicated by the lack of methods for objective quantitative assessment of qualitative characteristics of digital color halftone images.
The developed method of quantitative assessment of color characteristics of digital images by conversion of actinicity in values of effective densities provides optimal and comprehensive analysis of color rendering accuracy. The procedure consists in representation of color separation characteristics in a form of dependence of effective densities of the photographic image on grey-equivalent densities of the recorded object. It becomes possible to numerically evaluate imperfections of color rendering in a digital color photographic image.
The developed assessment procedure has become the basis for implementation of a new method for correcting color rendering imperfections with the help of compensatory corrective images ensuring elimination of the imperfection of insufficient color. The correction effect is provided by the physical content of compensatory images which contain effective densities for the separated colors which are absent in digital photographic images because of non-isoactinism of isochrome colors.
The new technology for correcting color rendering is implemented in the developed Image Redactor specialized software. Effectiveness of the described method was proved on the basis of analysis of images processed in the created software product according to the method of graphical representation of color separation characteristics described in the paper. Color separation matrices indicate a significant increase in useful contrasts of separated colors in comparison with similar characteristics of color rendering in images before their processing. This provides for the possibility of applying the developed method of correcting color rendering imperfections in the digital work flow of processing photographic images.
... The production involves self-assembling monolayers [16,17] which itself requires multiple processes to produce [19]. While the proposed sensor requires a complementary metal-oxide sensor (CMOS), they are also used for photography [22,36], so it is more widely available as an "off-the-shelf" product. This keeps costs lower for the proposed sensor. ...
The ingestion of the protozoan parasite Cryptosporidium, resulting in the associated disease cryptosporidiosis, can cause major problems if introduced into a water sup-ply for both animals and humans. This research focuses on the creation of a sensor to track and quantify the parasite with a digital camera system using Digital Inline Holographic Microscopy (DIHM) and software reconstruction. Since Cryptosporid-ium oocysts are not single celled and can be around 4–8µm in diameter, they are eas-ily detected with the DIHM at various depths within a 3.5mL cuvette. As the sen-sor is improved by modifications, it could pick up behavior of movement and sizes of particles measured to positively identify the particle(s) being tracked as Crypto-sporidium as others have achieved on Escherichia coli and other microorganisms. A significant advantage of this technique is the resulting sensor costs significantly less than traditional microscopes used in laboratory tests for detecting Cryptosporidium, or other methods like USEPA Method 1623 and can provide results within minutes. The sensor is a stellar alternative to current methods in detecting and quantifying Cryptosporidium.
... With this process, the CMOS approach is more flexible because each pixel can be read individually to get the data and convert it to an image. By this manufacturing process, CMOS image sensors can access signals at much high speed as compared to CCD [6]. CMOS sensors are more used in the still photography cameras and where the cost of the equipment also has to keep low. ...
... The charge-coupled device (CCD)-based optical temperature measurement technology combines the traditional radiation principle, modern photoelectric conversion principle, and digital image processing technology, and has the advantage of a non-contact, fast response, small error, and real-time dynamic measurement. The working principle of the CCD image sensor is [1][2][3][4][5]: When external light ...
The analysis of in-cylinder combustion temperatures using flame image processing technology is reliable. This method can accurately, intuitively, and in real time obtain the temperature field distribution law of the combustion flame in the cylinder, so we can more deeply understand the characteristics of the combustion process of internal combustion engines. In this paper, a high-speed charge-coupled device (CCD) camera is used to record an in-cylinder combustion image, which is calculated and corrected according to the principle of three primary color temperature measurement, and the temperature field distribution of the combustion flame in the diesel engine cylinder is analyzed in detail. In addition, the temperature of the typical combustion flame images under the open-cycle and closed cycle conditions is compared by the CMS2002 measurement and MATLAB program, respectively. The results show that the accuracy of the MATLAB program is acceptable in general but not entirely acceptable in a few ways.
... On the other hand, CCD technology has a high dynamic range and higher image quality in low light environments. The differences of both technologies begin to overlap and it is expected that in the future, CMOS technology will replace CCD [12,13]. ...
This paper presents a systematic review of the perception systems and simulators for autonomous vehicles (AV). This work has been divided into three parts. In the first part, perception systems are categorized as environment perception systems and positioning estimation systems. The paper presents the physical fundamentals, principle functioning, and electromagnetic spectrum used to operate the most common sensors used in perception systems (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK, etc.). Furthermore, their strengths and weaknesses are shown, and the quantification of their features using spider charts will allow proper selection of different sensors depending on 11 features. In the second part, the main elements to be taken into account in the simulation of a perception system of an AV are presented. For this purpose, the paper describes simulators for model-based development, the main game engines that can be used for simulation, simulators from the robotics field, and lastly simulators used specifically for AV. Finally, the current state of regulations that are being applied in different countries around the world on issues concerning the implementation of autonomous vehicles is presented.
Modern imaging technology, by exposure and subsequent readout from image sensors, has limited the existing frame rate in real-time scenes. In this article, we present an architecture based on computing in sensor array that can achieve higher frame rates than conventional cameras. This approach fuses the architecture with neural network algorithms for compressed sensing and computational imaging. It achieves a mean squared error of 10
−2
with fewer weights and sampling numbers (10%~40% of original data). It samples lower data to reconstruct images through fast recovery with an elapsed time of hundred microseconds. The feasibility has been verified through the encoded photodetector array chip consisting of 16×16 dual-gate silicon photodiodes. This type of chips represents a highly promising technology for constructing image sensors that delivers high-speed imaging capability of >10000 fps, which may also show potential superiority in terms of noise resistance and dynamic range.
In recent years, the progress in smartphone technology has made them affordable and versatile platforms for various applications, including chemical analysis. This article explores the evolving landscape of smartphone-assisted colorimetry, focusing on its role in the detection of drugs and food coloring. We provide a comprehensive overview of the current state of smartphone-assisted colorimetry. Our review focuses on smartphone-based colorimetry methods, explicitly examining the measurement of light absorption through smartphone apps and the accompanying instruments and software used in these processes. We also discuss the advantages and disadvantages of using smartphones for colorimetric assays. Additionally, we present successful real-world applications of smartphones for quantifying the concentration of specific chemicals in diverse samples through colorimetric assays. Finally, we explore potential future directions for smartphone-based colorimetry, offering insights into how this technology could further revolutionize the field of chemical analysis. In conclusion, integrating smartphones into colorimetry shows excellent promise as an affordable tool for detecting narcotics and food coloring, potentially reshaping the landscape of chemical analysis.
High-precision cylindrical parts are critical components across various industries including aerospace, automotive, and manufacturing. Since these parts play a pivotal role in the performance and safety of the systems they are integrated into, they are often subject to stringent quality control measures. Defects on the interior and exterior wall surfaces of these cylindrical parts can severely undermine their function, leading to degraded performance, increased wear, and even catastrophic failures in extreme cases. This article aims to comprehensively summarize the task definition, challenges, mainstream methods, public datasets, evaluation metrics, and other aspects of surface defect detection for high-precision cylindrical parts, in order to help researchers quickly grasp this field. Specifically, the background and characteristics of industrial defect detection are first introduced. Owing to the unique geometric features of cylindrical part surfaces, algorithms and equipment for image data acquisition used in surface defect detection are elaborated in detail. This article presents an extensive overview of state-of-the-art surface defect detection techniques designed for high-precision cylindrical components, all rooted in deep learning. The methods are systematically classified into three main categories: fully supervised, unsupervised, and alternative approaches, based on their data labeling strategies. Additionally, the paper conducts a comprehensive analysis within each category, shedding light on their unique strengths, limitations, and practical use cases. Concluding the discussion, the paper provides insights into future development trends and potential research directions in this field that will lead to manufacturing innovation.
Agriculture is an important pillar of world development, and smart agriculture is an emerging paradigm in current practices. RGB Images contain rich information and play an increasingly important role in various scenes of smart agriculture. Image sensing, transmission and other key aspects rely on agricultural Internet of Things infrastructure. However, images contain substantial amounts of data, which poses new challenges to traditional Internet of Things frameworks. In this paper, using smart agriculture as the background, the research status of RGB image-based applications in agricultural Internet of Things is reviewed from different perspectives. Firstly, a new RGB image-based Internet of Things framework based on cloud edge computing is proposed. The driving technologies of RGB image information collections, transmissions and applications are summarized. Then, based on the previous research, an agricultural image Internet of Things application case is presented. Finally, the challenges of RGB image-based agricultural Internet of Things applications are discussed.
In this paper, we have investigated gamma radiation effects on two identical CCD cameras under ‘power on’ and ‘power off’ conditions. The cameras were irradiated up to a total ionizing dose of 40 krad at a dose rate of 20 krad/hr using a Co-60 gamma source. The images captured at regular intervals with both cameras were analyzed using image quality analysis techniques to evaluate the performance degradation of the cameras with gamma dose. The parameters such as mean value, mode value, variance, number of bright pixels, peak signal to noise ratio and structural similarity index matrix were calculated from the image data. All statistical parameters showed that for the same gamma dose, the degradation of the camera under ‘power on’ condition was higher than that of the camera which was irradiated under ‘power off’ condition. The image analysis techniques presented in this paper could be helpful for assessing the health or useful life of the cameras during operation in nuclear facilities.
Geleneksel fotoğraf makinelerinde görüntü kimyasal yapıya sahip film yüzeyine aktarılırken, dijital fotoğraf makinelerinde ise görüntü, piksel mantığı ile çalışan algılayıcı üzerine aktarılmaktadır. Bu dönüşüm aşamasında konvansiyonel makinelerde filmde bulunan gümüş halojenürlere bağlı olarak ışık duyarlılığının gösterildiği DIN/ASA değeri tanımlanırken, dijital kullanımda ise DIN/ASA değerinin yerine, sensörün ışığa duyarlılığı olarak tanımlanan ISO değeri kullanılmaktadır. Fotoğraf çekiminde kullanılan ayarlar diyafram, obtüratör, white balance (beyaz ayarı) ve ISO'dur. Işık miktarının az olduğu ortamlarda, yüksek ISO değerleri kullanılmaktadır. Fakat yüksek ISO değerlerinin kullanılması fotoğrafta gürültü (noise) hatasını beraberinde getirmektedir. Bu durum özellikle ışık miktarının az olduğu müze, saray gibi kapalı alan çekimlerinde, orijinale yakın renk değerlerine sahip fotoğrafların elde edilmesinde problem olarak ortaya çıkar. Ayrıca, çekilen fotoğrafların hem dijital ortamlarda kullanılması için hem de basılabilmesi için renk evrenlerinin mümkün olduğunca geniş olması beklenir. Bu çalışmada, farklı ISO değerlerinin (100, 200, 400 ve 800), fotoğraf kalitesini nasıl etkilediği araştırılmıştır. Çalışma sonucunda, çekimi gerçekleştirilen fotoğrafların renklerinin ISO değerine bağlı olarak orijinal üzerindeki renklerden uzaklık değerleri 1 Makale yazımı yazar etki oranı: 1.yazar: %50, 2. yazar: %50.
Utilizing 3D point cloud data has become an urgent need for the deployment of artificial intelligence in many areas like facial recognition and self-driving. However, deep learning for 3D point clouds is still vulnerable to adversarial attacks, e.g., iterative attacks, point transformation attacks, and generative attacks. These attacks need to restrict perturbations of adversarial examples within a strict bound, leading to the unrealistic adversarial 3D point clouds. In this paper, we propose an Adversarial Graph-Convolutional Generative Adversarial Network (AdvGCGAN) to generate visually realistic adversarial 3D point clouds from scratch. Specifically, we use a graph convolutional generator and a discriminator with an auxiliary classifier to generate realistic point clouds, which learn the latent distribution from the real 3D data. The unrestricted adversarial attack loss is incorporated in the special adversarial training of GAN, which enables the generator to generate the adversarial examples to spoof the target network. Compared with the existing state-of-art attack methods, the experiment results demonstrate the effectiveness of our unrestricted adversarial attack methods with a higher attack success rate and visual quality. Additionally, the proposed AdvGCGAN can achieve better performance against defense models and better transferability than existing attack methods with strong camouflage.
Over the last decade, the Advanced Driver Assistance System (ADAS) concept has evolved prominently. ADAS involves several advanced approaches such as automotive electronics, vehicular communication, RADAR, LIDAR, computer vision, and its associated aspects such as machine learning and deep learning. Of these, computer vision and machine learning-based solutions have mainly been effective that have allowed real-time vehicle control, driver-aided systems, etc. However, most of the existing works deal with ADAS deployment and autonomous driving functionality in countries with well-disciplined lane traffic. These solutions and frameworks do not work in countries and cities with less-disciplined/ chaotic traffic. Hence, critical ADAS functionalities and even L2/ L3 autonomy levels in driving remain a major open challenge. In this regard, this work proposes a novel framework called Auto-Alert. Auto-Alert performs a two-stage spatial and temporal analysis based on external traffic environment and tri-axial sensor system for safe driving assistance. This work investigates time-series analysis with deep learning models for driving events prediction and assistance. Further, as a basic premise, various essential design considerations towards the ADAS are discussed. Significantly, the Convolutional Neural Network (CNN) and Long-Short-Term-Memory (LSTM) models are applied in the proposed Auto-Alert. It is shown that the LSTM outperforms the CNN with 99% for the considered window length. Importantly, this also involves developing and demonstrating an efficient traffic monitoring and density estimation system. Further, this work provides the benchmark results for Indian Driving Dataset (IDD), specifically for the object detection task. The findings of this proposed work demonstrate the significance of using CNN and LSTM networks to assist the driver in the holistic traffic environment.
Multispectral imaging (MI) techniques are being used very often to identify different properties of nature in several domains, going from precision agriculture to environmental studies, not to mention quality inspection of pharmaceutical production, art restoration, biochemistry, forensic sciences or geology, just to name some. Different implementations are commercially available from the industry and yet there is quite an interest from the scientific community to spread its use to the majority of society by means of cost effectiveness and ease of use for solutions. These devices make the most sense when combined with unmanned aerial vehicles (UAVs), going a step further and alleviating repetitive routines which could be strenuous if traditional methods were adopted. In this work, a low cost and modular solution for a multispectral camera is presented, based on the use of a single panchromatic complementary metal oxide semiconductor (CMOS) sensor combined with a rotating wheel of interchangeable band pass optic filters. The system is compatible with open source hardware permitting one to capture, process, store and/or transmit data if needed. In addition, a calibration and characterization methodology has been developed for the camera, allowing not only for quantifying its performance, but also able to characterize other CMOS sensors in the market in order to select the one that best suits the budget and application. The process was experimentally validated by mounting the camera in a Dji Matrice 600 UAV to uncover vegetation indices in a reduced area of palm trees plantation. Results are presented for the normalized difference vegetation index (NDVI) showing a generated colored map with the captured information.
Monitoring public space with imaging sensors to perform an object- or person-tracking is often associated with privacy concerns. We present a Dynamic Vision Sensor (DVS) based approach to achieve this tracking that does not require the creation of conventional grey- or color images. These Dynamic Vision Sensors produce an event-stream of information, which only includes the changes in the scene. The presented approach for tracking considers the scenario of fixed mounted sensors. The method is based on clustering events and tracing the resulting cluster centers to accomplish the object tracking. We show the usability of this approach with a first proof-of-concept test.
An imaging system comprises a multi-channel matrix array of CCD devices wherein a number of sensor cells (pixels) in each channel are subdivided and operated in discrete intercoupled groups of subarrays with a readout CCD shift register terminating each end of the channels. Clock voltages, applied to the subarrays, selectively cause charge signal flow in each subarray in either direction independent of the other subarrays. By selective application of four phase clock voltages, either one, two or all three of the sections subarray sections cause charge signal flow in one direction, while the remainder cause charge signal flow in the opposite direction. This creates a form of selective electronic exposure control which provides an effective variable time delay and integration of three, six or nine sensor cells or integration stages. The device is constructed on a semiconductor sustrate with a buried channel and is adapted for front surface imaging through transparent doped tin oxide gates.
This paper provides an overview of both CCD (charged coupled device) and CMOS (complimentary metal oxide semiconductor) imaging array technologies. CCDs have been in existence for nearly 30 years and the technology has matured to the point where very large, consistent (low numbers of defects) devices can now be produced. However, CCDs suffer from a number of drawbacks, including cost, complex power supplies and support electronics. CMOS imaging arrays, on the other hand, are still in their infancy, but are set to develop rapidly and offer a number of potential benefits over CCDs. This review provides an overview of both CCD and CMOS imaging technology, and includes explanations of how images are captured and read out from the imaging arrays. Also covered are issues such as performance characteristics, cost considerations and the future of imaging arrays. This review does not provide details of colour sensors, colour filter arrays and colour interpolation, etc., as these will be the subject of a separate report.
Discussing Image sensor Evolution and the Future of Imaging at the ISSCC
- Tomyoki Suzuki
Tomyoki Suzuki, Discussing Image sensor Evolution and the Future of
Imaging at the ISSCC 2010 ISSCC 2010 International Conference, Feb
7 to 11, 2010.
Introduction to CCDs
- Claudio Cumani
Claudio Cumani(2004),Introduction to CCDs,Garding,July 2006.
The university of oregon physics department website; Evolving towards the perfect
The university of oregon physics department website; Evolving towards
the perfect.CCD; 1997 ; http://zebu.uoregon.edu/ccd.html
Gamal,Introduction to image sensor
- A El
A. El. Gamal,Introduction to image sensor.