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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.
... 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.
... 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.
... 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.
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.
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
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.
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.
This paper optimizes the buried channel charge-coupled device (BCCD) structure fabricated by complementary metal oxide semiconductor (CMOS) technology. The optimized BCCD has advantages of low noise, high integration and high image quality. The charge transfer process shows that interface traps, weak fringing fields and potential well between adjacent gates all cause the decrease of charge transfer efficiency (CTE). CTE and well capacity are simulated with different operating voltages and gap sizes. CTE can achieve 99.999% and the well capacity reaches up to 25 000 electrons for the gap size of 130 nm and the maximum operating voltage of 3 V.
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
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Introduction to CCDs
- Claudio Cumani
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The university of oregon physics department website; Evolving towards the perfect
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Gamal,Introduction to image sensor
- A El
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