Image Processing - Science topic
All kinds of image processing approaches.
Questions related to Image Processing
If we acquire a tomography dataset, we can extract alot of physical properties from it, including porosity and permeability. These properties are not directly measured using conventional experiment. Instead, they are calculated using different image processing algorithms. To this end, is there any guideline on how to report such results in terms of significant digits?
As AI continues to progress and surpass human capabilities in various areas, many jobs are at risk of being automated and potentially disappearing altogether. Signal processing, which involves the analysis and manipulation of signals such as sound and images, is one area that AI is making significant strides in. With AI's ability to adapt and learn quickly, it may be able to process signals more efficiently and effectively than humans. This could ultimately lead to fewer job opportunities in the field of signal processing, and a shift toward more AI-powered solutions. The impact of automation on the job market is a topic of ongoing debate and concern, and examining the potential effects on specific industries such as signal processing can provide valuable insights into the future of work.
In image processing and image segmentation studies are these values the same?
DSC (Dice similarity coefficient)
Can we convert them together?
Dear Colleagues, I started this discussion to collect data on the use of the Azure Kinect camera in research and industry. It is my intention to collect data about libraries, SDKs, scripts and links, which may be useful to make life easier for users and developers using this sensor.
Notes on installing on various operating systems and platforms (Windows, Linux, Jetson, ROS)
- Azure Kinect camera setup (automated scripts for Linux). https://github.com/juancarlosmiranda/azure_kinect_notes
- Azure Kinect ROS Driver. https://github.com/microsoft/Azure_Kinect_ROS_Driver
SDKs for programming
- Microsoft SDK C/C++. https://learn.microsoft.com/en-us/azure/kinect-dk/sensor-sdk-download
- Azure Kinect Body Tracking SDK. https://learn.microsoft.com/en-us/azure/kinect-dk/body-sdk-download
- Github Azure Kinect SDK. https://github.com/microsoft/Azure-Kinect-Sensor-SDK
- KinZ an Azure Kinect toolkit for Python and Matlab.
- pyk4a - a simple and pythonic wrapper in Python 3 for the Azure-Kinect-Sensor-SDK. https://github.com/etiennedub/pyk4a
Tools for recording and data extraction
- Azure Kinect DK recorder. https://learn.microsoft.com/en-us/azure/kinect-dk/azure-kinect-recorder
- Azure Kinect Viewer. https://learn.microsoft.com/en-us/azure/kinect-dk/azure-kinect-viewer
- ak-sm-recorder. https://pypi.org/project/ak-sm-recorder/
- ak-frame-extractor. https://pypi.org/project/ak-frame-extractor/
Demo videos to test the software (update 08/03/2023)
- AK_FRAEX - Azure Kinect Frame Extractor demo videos. https://doi.org/10.5281/zenodo.6968103
Papers, articles (update 22/03/2023)
- Experimental Procedure for the Metrological Characterization of Time-of-Flight Cameras for Human Body 3D Measurements. [
How Thermal Image Processing works in Agriculture sector?
I am working on a research project that involves detecting cavities or other teeth problems in panoramic X-rays. I am looking for datasets that I can use to train my convolutional neural network. I have been searching on the internet for such datasets, but I didn't find anything so far. Any suggestions are greatly appreciated! Thank you in advance!
Need to publish research paper in impact factor journal having higher acceptance rate and faster review time.
How do you think artificial intelligence can affect medicine in real world. There are many science-fiction dreams in this regard!
but how about real-life in the next 2-3 decades!?
As my protein levels appears to be varying in different cell types and different layers and localization (cytoplasm/nucelus) of the root tip of Arabidopsis (in the background of Wild type and mutant plants).
I wonder what should be my approach to compare differences in protein expression levels and localization between two genotypes.
I take Z-stack in a confocal microscope, usually I make a maximum intensity profile of Z- stack and try to understand the differences but as the differences are not only in intesities but also cell types and layers in that case how should I choose the layers between two samples?
My concern is how to find out exact layers between two genotypes as the root thickness is not always same and some z-stacks for example have 55 slices and some have 60.
I am trying to open fMRI images in my PC but (I think) no appropriate software is present in PC. Hence I am not able to open indidial images in my PC.
I have a photo of bunches of walnut fruit in rows and I want to develop a semi-automated workflow for ImageJ to label them and create a new image from the edges of each selected ROI.
What I have done until now is Segmenting walnuts from the background by suitable threshold> then select the all of the walnuts as a single ROI>
Now I need to know how can I label, the different regions of ROI and count them in numbers to add to the ROI manager. Finally, these ROIs must be cropped from their edges and new image from each walnut should save individually.
Thoughts on how to do this, as well as tips on the code to do so, would be great.
Hi. I have written a paper in the field of image processing that is 21 pages long on a double column IEEE template. I'm a beginner in the publishing world and only after finishing the paper I realized that the journal to which I was wanting to submit (IEEE TIP) has a 14 pages limit with a $220/page fee for the number of pages exceding 11 (very salty in the currency of my country).
I think I can reduce the number of pages to arround 15 by removing some figures and non essential paragraphs. But it would still be too large for submission on TIP and other IEEE journals.
Do you recommend me any good journal that would accept a 15+ pages research paper in the field of image processing, with no fee or at least being affordable for a student?
Basically I was Interested in Skin Diseases Detection Using Image Processing
Kindly suggest me technology to be used and a research problem
I'm currently doing research in image processing using tensors, and I found that many test images repeatedly appear across related literature. They include: Airplane, Baboon, Barbara, Facade, House, Lena, Peppers, Giant, Wasabi, etc. However, they are not referenced with a specific source. I found some of them from the SIPI dataset, but many others are missing. I'm wondering if there are "standards" for the selection of test images, and where can the standardized images be found. Thank you!
I’m currently training a ML model that can estimate sex based on dimensions of proximal femur from radiographs. I’ve taken x-ray images from ALL of the samples in the osteological collection in Chiang Mai, left side only, which came to a total of 354 samples. I also took x-ray photos of the right femur and posterior-anterior view of the same samples (randomized, and only selective few n=94 in total) to test the difference, dimension wise. I have exhausted all the samples for training the model and validating (5-fold), which results in great accuracy of sexing. So, I am wondering whether it is appropriate to test the models with right-femur and posterior-anterior view radiographs, which will then be flipped to resemble left femur x-ray images, given the limitations of our skeletal collection?
I have a brain MRI dataset which contains four image modalities: T1, T2, Flair and T1 contrast-enhanced. From this dataset, I want to segment the Non-Enhancing tumor core, Peritumoral Edema and GD-enhancing tumor. I'm confused about which modality I should use for each of the mentioned diseases.
I will be thankful for any kind of help to clear up my confusion.
Say I have a satellite image of known dimensions. I also know the size of each pixel. The coordinates of some pixels are given to me, but not all. How can I calculate the coordinates for each pixel, using the known coordinates?
Hi everyone, so in the field of magnetometry there is a vast body of work relating to the identification of various ferromagnetic field conditions but very little devoted to that of diamagnetic anomalies in the datasets both for airborne and satellite sources. For my current application were utilizing satellite based magnetometry data and are already working on image process algorithms that can enhance the spatial resolution of the dataset for more localized ground-based analysis. However, we're having difficulties in creating any form of machine learning system that can identify the repelling forces of diamagnetic anomalies underground primarily due to the weakness of the reversed field itself. I was just wondering if anyone had any sources relating to this kind of remote sensing application or any technical principles that we could apply to help jumpstart the projects development. Thanks for any and all information.
Hello dear RG community.
I started working with PIV some time ago. It's being an excruciating time of figuring out how to deal with the thing (even though I like PIV).
Another person I know spent about 2.5 months figuring out how to do smoke viz. And yet another person I know is desperately trying to figure out how to do LIF (with no success so far).
As a newcomer to the area I can't emphasize how valuable any piece of help is.
I noticed there is not one nice forum covering everything related to flow visualization.
There are separate forums on PIV analysis and general image processing (let me take an opportunity here to express my sincere gratitude to Dr. Alex Liberzon for the OpenPIV Google group that he is actively maintaining). Dantec and LaVision tech support is nice indeed.
But, still, I feel like I want one big forum about absolutely anything related to flow vis: how to troubleshoot hardware, how to pick particles, best practices in image preprocessing, how to use commercial GUI, how to do smoke vis, how to do LIF, infraction index matching for flow vis in porous media, PIV in very high speed flows, shadowgraphing, schlieren and so on.
Reading about theory of PIV and how to do it is one thing. But when it comes to obtaining images - oh, that can easily turn to a nightmare! I want a forum where we can share practical skills.
I'm thinking about creating a flow vis StackExchange website.
Area51 is a part of StackExchange where one can propose a StakExchange website. They have pretty strict rules for proposals. Proposals have to go through 3 stages of life cycle before they are allowed to become full-blown StackExchange websites. The main criteria is how many people visit the proposed website, ask and answer questions.
Before a website is proposed, one need to ensure there are people interested in the subject. Once the website has been proposed, one has 3 days to get at least 5 questions posted and answered, preferably, by the people who had expressed their interest in the topic. If the requirement is fulfilled the proposal is allowed to go on.
Thus, I'm wondering what does dear RG community think? Are there people interested in the endeavor? Is there a "seeding community" of enthusiasts who are ready to post and answer at least 5 questions withing the first 3 days?
If so, let me know in the comments, please. I will propose a community and post the instructions for you how to register in Area51, verify your email and post and answer the questions.
Bear in mind, that since we have not only to post the questions but also answer them the "seeding community" should better include flow vis experts.
How to plot + at center of circle after getting circle from Hough transform?
I obtained the center in workspace as "centers [ a, b] ".
When I am plotting with this command
plot(centers ,'r+', 'MarkerSize', 3, 'LineWidth', 2);
then I get the '+' at a and b on the same axis.
2 Logistic chaotic sequences generation, we are generating two y sequence(Y1,Y2) to encrypt a data
2D logistic chaotic sequence, we are generating x and y sequence to encrypt a data
whether the above statement is correct, kindly help in this and kindly share the relevant paper if possible
I have recently started my research in detecting and tracking brain tumors with the help of artificial intelligence, which includes image processing.
What part of this research is valuable, and what do you suggest for the most recent part that is still useful for a PhD. research proposal?
Thank you for participating in this discussion.
website for researching a special issue dates
I am trying to make generalizations about which layers to freeze. I know that I must freeze feature extraction layers but some feature extraction layers should not be frozen (for example in transformer architecture encoder part and multi-head attention part of the decoder(which are feature extraction layers) should not be frozen). Which layers I should call “feature extraction layer” in that sense? What kind of “feature extraction” layers should I freeze?
As a generative model, GAN is usually used for generating fake samples but not classification
I have performed a Digital Image Correlation test on a rectangular piece of rubber to test the authenticity of my method. However, I faced this chart most of the time. Can anyone show me why this is happening? I am using Ncorr and Post Ncorr for Image processing.
Monkeypox Virus is recently spreading very fast, which is very alarming. Awareness can assist people in reducing the panic that is caused all over the world.
To do that, Is there any image dataset for monkeypox?
These days machine learning application in cancer detection has been increased by developing a new method of Image processing and deep learning. In this regard, what is your idea about a new image processing method and deep learning for cancer detection?
Thank you in advance for participating in this discussion.
As a student who wants to design a chip for processing CNN algorithms, I ask my question. If we want to design a NN accelerator architecture with RISC V for a custom ASIC or FPGA, what problems or algorithms do we aim to accelerate? It is clear to accelerate the MAC (Multiply - Accumulate) procedures with parallelism and other methods, but aiming for MLPs or CNNs makes a considerable difference in the architecture.
As I read and searched, CNN are mostly for image processing. So anything about an image is usually related to CNN. Is it an acceptable idea if I design architecture to accelerate MLP networks? For MLP acceleration which hw's should I work on additionally? Or is it better to focus on CNN's and understand it and work on it more?
I have a large DICOM dataset, around 200 GB. It is stored in Google Drive. I train the ML model from the lab's GPU server, but it does not have enough storage. I'm not authorized to attach an additional hard drive to the server. Since there is no way to access Google Drive without Colab (if I'm wrong, kindly let me know), where can I store this dataset so that I will be able to access it for training from the remote server?
Could you tell me please what is the effect of electromagnetic waves on a human cell? And how to model the effect of electromagnetic waves on a human cell using image processing methods?
I am currently working on Image Processing of Complex fringes using MATLAB. I have to do the phase wrapping of images using 2D continuous wavelet transform.
I have a salt(5grains) which undergoes hydration and dehydration for 8 cycles. I have pictures of them swelling and shrinking taken every five minutes under microscope. I can see in the video that salt is swelling and shrinking if i compile the images. But I need to quantify how much increase or decrease in size takes place. Can anyone explain about how I can make use of the pictures
I am working on a classification task and I used 2D-DWT as a feature extractor. I want to ask about more details why I can concatenate 2D-DWT coefficients to make image of features. I am thinking to concatenate these coefficients(The horizontal,vertical and diagonal coeeficients) to make an image of features then fed this to CNN but I want to have an convincing and true evidence for this new approach.
Any short introductory document from image domain please.
I would appreciate it if someone can help me choose a topic in AI Deep Learning or Machine Learning.
I am looking for an Algorithm that can be used in different application and have some issues in terms of accuracy and result, to work on its improvement.
recommend me some papers that help me to find some gaps so I can write my proposal.
I'm looking for the name of an SCI/SCIE journal with a quick review time and a high acceptance rate to publish my paper on image processing (Image Interpolation). Please make a recommendation.
I am looking for experts in area of Biomedical Image Processing.
Any recommendations ?
As you can see that the image is taken by changing the camera angle to include the building in the scene. The problem with this is that the measurements are not accurate with the perspective view.
How can I fix this image for the right perspective (centered)?
Red Blood Cells, White Blood Cells, Sickle Cells.
Suppose I use laplacian pyramid for image denoising application, how would it be better than wavelets? I have read some documents related to laplacian tools in which laplacian pyramids are said to have better selection for signal decomposition than wavelets.
I would like to know about the best method to follow for doing MATLAB based parallel implementation using GPU of my existing MATLAB sequential code. My code involves several custom functions, nested loops.
I tried coverting to cuda-mex function using MATLAB's GPU coder, but I observed that it takes much more time (than CPU) to run the same function.
Proper suggestions will be appreciated.
Can you guys tell me the problems or limitations of Computer Vision in this era, on which no one has yet paid heed or problems on which researchers and Industries are working but still didn't get success?
Thanks in Advance!
If you are researcher who is studying or already published on Industry 4.0 or digital transformation topic, what is your hottest issue in this field?
Your answers will guide us in linking the perceptions of experts with bibliometric analysis results.
Thanks in advance for your contribution.
Lane detection is a common use case in Computer Vision. Self-driving cars rely heavily on seamless lane detection. I attempted a road lane detection inspired use case, using computer vision to detect railway track lines. I am encountering a problem here. In the case of road lane detection, the colour difference between road (black) and lane lines (yellow/ white) makes edge detection and thus lane detection fairly easy. Meanwhile, in railway track line detection, no such clear threshold for edge detection exists and the output is as in the second image. Thus making the detection of track lines unclear with noise from the track slab detections etc. This question, therefore, seeks guidance/ advice/ Knowledge exchange to solve this problem. Any feedback on the approach taken to attempt the problem is highly appreciated. Tech: OpenCV
I'm about to start some analyses of vegetation indexes using Sentinel-2 imagery through Google Earth Engine. The analyses are going to comprise a series of images from 2015/2016 until now, and some of the data won't be available in Level-2A of processing (Bottom-of-Atmosphere reflectance).
I know there are some algorithms to estimate BOA reflectance. However, I don't know how good these estimates are, and the products generated by Sen2Cor look more reliable to me. I've already applied Sen2Cor through SNAP, but now I need to do it in a batch of images. Until now, I couldn't find any useful information about how to do it in GEE (I'm using the Python API).
I'm a beginner, so all tips are going to be quite useful. Is it worth applying Sen2Cor or the other algorithms provide good estimates?
Thanks in advance!
I am publishing paper in scopus journal and got one comment as follows:
Whether the mean m_z is the mean within the patches 8x8? If the organs are overlap then how adaptive based method with patches 8x8 is separated? No such image has been taken as a evidence of the argument. Please incorporate the results of such type of images to prove the effectiveness of the proposed method. One result is given which are well separated.
Here I am working on method which takes patches of given image and takes mean of them. This mean is used for normalizing the data.
However, I am unable to understand the meaning of second sentence. As per my knowledge, the MRI image is kind of see through, so how will be any overlap of organs?
During preprocessing medical image data different techniques should be considered such as cropping, filtering, masking, augmentation. My query is, which techniques are frequently applied to medical image datasets during pre-processing?
I'm looking to generate synthetic diffusion images from T1 weighted images of the brain. I read that diffusion images are a sequence of T2 images but with gradients. Maybe could be something related to this. I'm not sure how to generate these gradients too. I'm trying to generate "fake" diffusion images from T1w because of the lack of data from the subjects I'm evaluating.
Can someone please help me?
I have been working on computer vision. I used datasets from Kaggle or other sites for my projects. But now I want to do lane departure warning, and real-time lane detection with real-time conditions(illuminations, road conditions, traffic, etc.). Then the idea to use simulators comes to my mind but there are lots of simulators on online but I'm confused about which one would be suitable for my work!
It would be very supportive if anyone guide me through picking up the best simulator for my works.
Is it because the imaging equation used by the color constancy model is built on RAW images? Or is it because the diagonal model can only be applied to RAW images? When we train a color constancy model using sRGB images, can we still use certain traditional color constancy models such as gamut mapping, correction moments, or CNN?
Could anyone suggest a software or code (R or Python) that is capable of recognizing bumblebees (recognizing only not identifying) from video recordings?
Greetings for the day,
With great privilege and pleasure, i request anyone belonging to Image Processing domain to review my Ph.D thesis. I hope you will be kind enough to review my research work. Please revert me back on my email id: firstname.lastname@example.org at your leisure.
Thanking you in advance.
Hi. I'm working on 1000 images of 256x256 dimensions. For segmenting I'm using segnet, unet and deeplabv3 layers. when I trained my algorithms it takes nearly 10 hours of training. I'm using 8GB RAM with a 256GB SSD laptop and MATLAB software for coding. Is there any possibility to speed up training without GPU?
I am researching handwriting analysis using image processing techniques.
Does anybody can recommend me a tool that coul extract (segment) pores (lineolae) from the following image of a diatom valve?
I mean an ImageJ or FiJi plugin or any other software that can solve this task.
I'd like to measure frost thickness on fins of a HEX based on GoPro frames.
I got the ImageJ software. But I don't know if there is a way to select a zone, (a frosted fin) and deduce the average length in one direction.
Currently I do random measurements on the given fin and do the average. However, the random points may not be representative.
I attached two pictures of the fins and frost to illustrate my question.
In advance, thank you very much,
Currently, I'm working on a Deep Learning based project. It's a multiclass classification problem. The dataset can be found here: https://data.mendeley.com/datasets/s8x6jn5cvr/1
I have used Transfer Learning mostly, but couldn't able to get a higher accuracy on the test set. I have used Cross-Entropy and Focal Loss as loss functions. Here, I have 164 samples in the train set, 101 samples in the test set, and 41 samples in the validation set. Yes, about 33% of samples are in the test partition (data partition can't be changed as instructed). I could able to get an accuracy score and f1 score of around 60%. But how can I get higher performance in this dataset with this split ratio? Can anyone suggest me some papers to follow? Or any other suggestion? Suggest me some papers or guidance on my Deep Learning-based multiclass classification problem?
I am working on CTU (Coding Tree Unit) partition using CNN for intra mode HEVC. I need to prepare database for that. I have referred multiple papers for that. In most of papers they are encoding images to get binary labels splitting or non-splitting for all CU (Coding Unit) sizes, resolutions, and QP (Quantization Parameters).
If any one knows how to do it, please give steps or reference material for that.
In my research, I have created a new way of weak edge enhancement. I wanted to try my method on the image dataset to compare it with the active contour philosophy.
So, I was looking for images with masks, as shown in the below paper.
If you can help me to get this data, it would be a great help.
Thanks and Regards,
I'm looking for a PhD position and opportunity in one of the English speaking university in European countries (or Australia).
I majored in artificial intelligence. I am in the field of medical image segmentation and My thesis in master was about retinal blood vessels extraction based on active contour. Skilled in Image processing, machine learning, MATLAB and C++.
So could anybody helps me to find a prof and PhD position related on my skills in one of the English speaking university?
recently i am collecting red blood cells dataset for classifying into 9 categories of Ninad Mehendale research paper. can anyone suggest the dataset for Red Blood Cell Classification Using Image Processing and CNN this papeer?
There are shape descriptors: circularity, convexity, compactness, eccentricity, roundness, aspect ratio, solidity, elongation.
1) What are the real formulas for determining these descriptors?
2) circularity = roundness? solidity = ellipticity?
I compared lectures (M.A. Wirth*) with ImageJ (Fiji) user guide and completely confused: descriptors are almost completely different! Which source to trust?
*Wirth, M.A. Shape Analysis and Measurement. / M.A. Wirth // Lecture 10, Image Processing Group, Computing and Information Science, University of Guelph. – Guelph, ON, Canada, 2001 – S. 29
In the remote sensing application to a volcanic activity wherein, the objective is to determine the temperature, which portion (more specifically the range) of the EM spectrum can detect the electromagnetic emissions of hot volcanic surfaces (which are a function of the temperature and emissivity of the surface and can achieve temperature as high as 1000°C)? Why?
I have grayscale images obtained from SHG microscopy for human cornea collagen bundles, and I have them as tiff stack images and their Czi format. I want to convert those 2D images into a 3D volume but I could not find any method that can be done using MATLAB, Python, or any other program?
Hello dear researchers.
It seems that siam rpn algorithm is one of the very good algorithms for object tracking that its processing speed on gpu is 150 fps.But the problem is that if your chosen object is a white phone, for example, and you are dressed in white and you move the phone towards you, the whole bunding box will be placed on your clothes by mistake. So, low sensitivity to color .How do you think I can optimize the algorithm to solve this problem? Of course, there are algorithms with high accuracy such as siam mask, but it has a very low fps. Thank you for your help.
I'm trying to acquire raw data from Philips MRI.
I followed the save raw data procedures and then I obtained a .idx and a .log file.
I'm not sure if I implemented the procedure correctly.
Are .idx and .log file the file format of Philips MRI raw data?
If so, how to open these files? Is it possible to open these files in matlab?
How can I tell the distance and proximity as well as the depth of image processing for object tracking? One idea that came to my mind was to detect whether the object was moving away or approaching based on the size of the image.But I do not know if there is an algorithm that I can implement based on?
In fact, how can I distinguish the x, y, z coordinates from the image taken from the webcam?
Thank you for your help
What are the main image processing journals that publish work on the collection, creation and classification of medical imaging databases such as Medical Image Analysis Journal.
Thank you for your support,
I am using transfer learning using pre-trained models in PyTorch for the Image classification task.
When I modified the output layer of the pre-trained model (e,g, alexnet) as per our dataset and run the code for seeing the modified architecture of alexnet it gives output as "none".
Hi Everyone, I'm currently converting video into images where I noticed 85% of the images doesn't contain the object. Is there any algorithm to check whether an image contains an object or not using the objectness score?
Thanks in advance :)
I'm currently practising an object detection model which should detect a car, person, truck, etc. in both day and night time. Now, I have started gathering data for both day and night time. I'm not sure whether to train a separate model for daylight and another model for the night-light or to combine together and train it?
can anyone suggest to me the data distribution for each class at day and night light? I presume it should be a uniform distribution. Please correct me if I'm wrong.
Eg: for person: 700 images at daylight and another 700 images for nightlight
Any suggestion would be helpful.
Thanks in Advance.