Questions tagged [image-processing]

A form of signal processing where the input is an image. Usually treating the digital image as a two-dimensional signal (or multidimensional). This processing may include image restoration and enhancement (in particular, pattern recognition and projection).

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8 views

How many points needed to compute the Homography? [migrated]

I'm working on a project where i'm using planar homography. As seen in the above image, every point gives two equations and since the homography matrix has 8 degree of freedom, 4 points are enough to ...
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How kernalised correlation filter-tracker works opencv [closed]

I'm using KCF-Tracker to track small colored cars (see image below) As you know implementing KCF in OpenCV is straight forward: ...
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Replacing Random Forests with CNN [closed]

Supposing I have a set of optical images to classify in for ground occupation issues. this classification is done using some Random forest algorithm with iteration. I mean by that that each time the ...
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23 views

How to make use of ground truth data in image anomaly detection?

If I have an image dataset that consists of "normal", anomalous and ground truth image data, how do I make use of the ground truth data? To my understanding if I train an unsupervised ...
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Normalization and Standardization of color channels for Convolutional Neural Networks

I have created 2D heat maps with 3 color channels. On these heat maps, I will train CNN networks. The range of values in the three colors channels is very different. In the first channel the values ...
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Image intensity normalization in preprocessing

Suppose having two images on a given scale, for example it could be the classic [0-255], representing the same thing but with different value intensities, i.e. the first could have a maximum pixel ...
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How to use PCA for feature extraction?

So what I have to do is given n images for training and m images for testing, I have to build a model for classification. To do that I need to extract features from the images. Now the person under ...
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Evaluating classifier with additional data

I have a data analysis problem where I have a blackbox image processing software that detects certain defects (cracks, potholes, expected objects like manhole covers, foreign objects) on a straight ...
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Euclidian distance vs cosine similarity

Currently I'm working on facial recognition. If I use encoding/feature vectors of 2 images which method will prove more accuracy, L2 norm or cosine similarity and why? I read "ICA performs ...
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Independent and identically distributed data (images)?

If it is said that the data must be independent and identically distributed, and the data are images, then what exactly does it mean for images to be "independent and identically distributed"...
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Enforcing sparsity constraints that make use of spatial contiguity

I have a deep learning network that outputs grayscale image reconstructions. In addition to good reconstruction performance (measured through mean squared error or some other measure like psnr), I ...
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Data augmentations to mimic natural variations present satellite imagery

I'd like to apply some machine learning algorithms to satellite imagery that we've collected, but I want to encourage invariance to factors such as sunlight intensity, time of day, atmospheric ...
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Is it possible to classify images by vectorizing them (and achieve a good performance)?

Many applications of image classification involves convolutional neural network, where the image is treated directly as a 2D (or 3D, if multiple images) matrix. I wonder if images can be classified (...
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autoencoders for radiographs - do watermarks affect the performance considerably

I have to implement an autoencoder to reconstruct the input radiographs and do unsupervised feature learning in the process. However, the radiographs that I have contain some watermarks like X-ray ...
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Does it make sense computing the mean value of a set of MSE values?

First of all, thank you for your attention. One of my class projects asked me to quantify the asymmetry of 3 classes of moles, given a dataset. In order to do that, I estimated the MSE between a 2D ...
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Object Classification vs Object Detection

My problem statement is as follows: I've got some technical documents as JPEGs, mostly text, but with some standard pictograms. Each image does not need to have all the pictograms or any pictogram at ...
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Denoising 3D matrix

Are there any standard techniques I can use to denoise a 3D matrix? I hope to apply something like simple SVD denoising methods (e.g., reconstructed the images with salient singular values) to a 3D ...
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1answer
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Is there any relationshipe between image input dimension, filter/kernal size and feature map?

Is there any relation between image input dimension (height, width), filter/kernal size and feature map? if for example I have this code: ...
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Metrics for evaluating low contrast

Hi i want to ask question. I have a dataset consists of images. Some of the images have very low contrast. I want to be able to measure the contrast in my dataset not by visual observation but by a ...
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1answer
39 views

Which Object detection model will give the best result on images when the speed is not a problem for Text Images

I want to develop a model for cropping the equations from the Maths questions as people like me are struggling a lot for doing it manually for the research purpose. I want to know if we can do this? ...
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1answer
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Compare between two ways of defining CNN layers

We know that the parameter tuning of the neural network is somehow like dealing with a blackbox; there is never a unified model for every problem. To this end, I've always wondered if the following <...
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Contextual Attention method and dilated convolution

When do image inpainting project, I have a question about the role of dilated convolution and contextual attention maybe overlap. Below image, I have 2 brands, which is try to get more information ...
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Pixel-wise classification using deep learning network and some errors

and my implementation code has little problem and doesn't work and shows error of incompatible shape. ...
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What is the difference between HLC (Histogram of local features) , CSS ( color self-similarity) ans MDST (Max DisSimilarity of Different Templates)

I'm new to computer vision and have been researching for Master thesis purposes in Detection algorithms and the techniques used in each. As I arrived to the point where alot of papers showed the ...
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Latent Dimension For AutoEncoder network

I have been experimenting with auto-encoder network to build content based image search engine. While i have had early success, one of the question which I am still not been able to figure out is &...
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Is this formulation of image classification using least squares appropriate?

I want to detect sidewalks in aerial images using a simple least squares classifier. This can be done using a more sophisticated method using a library such as neat-EO, but I would like to implement ...
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1answer
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What are some ways to measure the width of desert roads in satellite images?

I'm interested to know what sort of software and/or concepts should I learn to be be able to get a computer to recognize desert roads in a satellite image and measure for example their average widths. ...
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Preprocessing on ImageNet for MobileNetV2

I have saved an ImageNet model in ONNX for MobileNetV2 by doing the following: ...
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Resize images before training object detection

I am training an object detector. I didn't resize my image before labeling because the of assumption that the model does this automatically to fit its input shape. ...
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RSGAN - how do you separate parts of an image using a VAE

Authors of this paper (RSGAN) mention they're able to use two autoencoders, one separating face from an image and the other one separating hair: They don't describe how this is being done and it isn'...
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How Milestone object detectors differ from each other?

I'm tracing the object detector types starting from traditional detectors like Viola Jones, then machine learning detectors and ending with deep learning by Yolov4. Therefore I've created a table that ...
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1answer
50 views

Is there an eigenfaces equivalent for PCA analysis of time series, eigen-time series?

I am trying to better understand PCA as applied to time series by drawing parallels with this explanation of PCA as applied to images of faces. In particular, I would like to visualize the resulting "...
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How can I add in the functionality “Not found” in k-nearest neighbor?

I'm building onto a image classification library called jFaces. It's made in 100% Java. It don't use Deep neural networks. Instead, it uses PCA and LDA together. Yes, it works. https://github.com/...
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Different cut aria effect in aligning and comparing two STL file with cloudcompare

I have one project for dental thesis which some aspect of it is not clear for me. In this project we need to compare one specific area of dental mold scan by cloudcompare software, so the area is ...
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Finding Patterns on Surface of Material

I recently got a set of images on which I need to find certain patterns (such as scratches or roughness). Now I have two types of surfaces. I would like to compare if these two surfaces exhibit the ...
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1answer
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How to change the mean of an image without changing the range

I'm working with a dataset of grayscale images (values ranging from [0,1]) and would like the average pixel intensity of each image to be the same (let's say 0.5). However, a simple multiplication ...
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How to calculate ROC curve at a threshold value

I have to calculate the ROC of 12 different videos. I have taken a code from this LINK. Following is there code of calculating TPR and FPR: ...
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Classification Loss result is either too small or too big as epoch get higher

I am doing some experiments for classifying color using BCElogitLoss on Pytorch. The label that I have are (not red-red, not blue-blue , not green -green) and the inputs are images. So when I start ...
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How to draw Receiver Operating Characteristics (ROC) of 34 video sequences using MatLab

I am working on video processing using MatLab R2017a. I have datasets containing 34 video sequences. I have to calculate the AUC of this datasets. As I know AUC is dependent upon the ROC. And ROC is a ...
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Best way to show agreement between two 2d arrays

This question might seem very simple but I just wanted to make sure that I am doing it right! :) I have two 2d numpy arrays, representing a climate variable on global scale calculated using two ...
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24 views

Can a neural network whose output is uniformly equal to zero learn its way out of it?

I am performing a regression task on sparse images. The images are a result of a physical process with meaningful parameters (actually, they are a superposition of cone-like shapes), and I am trying ...
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1answer
86 views

Real noise modeling/ noise map generation (image processing, deep learning)

I am working on a project with really noisy images. I have trained a detector that can detect the characters but fails in some cases (noise is high). So far I have gone through many denoising, ...
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How to standardize/normalize 16 bit images with a small standard deviation

I'm trying to detect silhouettes on thermal 60x80 and depth 480x640 images by using the SSD model. I have good results on thermal images, but realy poor results on depth images. I started to ...
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Keras validation accuracy is high, but per class F-score is poor

I am trying to identify species of animal in images. I am using keras with VGG16, imagenet weights and adding 3 layers of 512 nodes on top. In training, Keras/TensorFlow reports fairly high validation ...
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Optimizers settings in keras CNN when using augmentation

I'm training a CNN for multi-class image segmentation in keras. A standard 3D-Unet for brain MRI segmentation with a softmax output layer, but I think it's not relevant, mostly to learn the technique ...
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How is the distribution for a 3-channel colored image data set learned?

I understand how the distribution for a grayscale image data set is learned, but I'm not able to wrap my head around for the 3-channel or colored scenario. Here is my comprehension for the ...
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Text retrieval from an image is not appropriate

I have an image where it contains names of several resources. When I am trying to read the text from the image using R its not throwing how it is present in image. For instance J is reported as I Or ...
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Can Graph Neural Networks be better than Convolutional Neural Networks for computer vision tasks? [closed]

Recently, a strong trend in deep learning is the adoption of Graph Neural Networks for computer vision tasks (https://github.com/thunlp/GNNPapers#computer-vision). But the main question is could this ...
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How do I change my neural network from a classification task to a regression task?

I currently have a neural network that is doing a reasonable job in classifying an image into a number of classes although not that great. These classes however are essentially buckets on a floating ...
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1answer
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How to properly upscale images using deconvolutions

I have a dataset that has 32x32x3 images. However, I want to use models that were developed for 224x224x3 images, e.g. resnet. A common theme I see is that people resize 32x32x3 to 224x224x3, but this ...

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