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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4 views

How to choose detection probability of Joint Probability Data Association Filter (JPDAF)?

I want to know about the optimal value or optimal method for choosing or calculating detection probability $P_D$ of JPDAF. I am working on image processing. Kindly guide me. I have searched and found ...
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25 views

Alternative summary statistic for image resizing [closed]

I have a distribution of heights 90K images and I have the following statistical summary values: ...
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Calculate standard deviation for grayscale imagenet pixel values with rotation matrix and regular imagenet standard deviation

I want to train some models to work with grayscale images, which e.g. is useful for microscope applications. Therefore I want to train my model on graysale imagenet, using the pytorch grayscale ...
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Importance for Color in X ray imaging for Detection of Pneumonia

I want to apply Deep learning architectures for detection of Pneumonia on chest X-rays, Should I directly apply CNN on RGB images or I should convert RGB into grayscale image and then apply CNN. ...
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Image Classification Modeling: How to determine particle size from mobile phone image?

I am looking for modeling advise: Given a picture of particles that can be coarse or fine (think sea salt vs. table salt or fine sand vs soil), I'd like to predict the particle size. Two pictures of ...
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SIFT: why Gaussian blur is performed iteratively?

SIFT is the feature detector I am trying to implement for self-study purposes. But my question concerns the Gaussian blurring done as part of detecting the keypoints. Gaussian pyramid is constructed. ...
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How to choose the best segmentation model using the area under the precision recall curve, IOU and Dice metrics?

I am using several U-Net variants for a brain tumor segmentation task. I get the following values for the performance measures including Dice, IOU, Area under receiver-operating characteristic (AUC) ...
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Quick technique for comparing images better than MSE

I have been using Structural Similarity Index (through tensorflow) for comparing images, however it takes too long. I was wondering if there is an alternative technique that doesn't take so much time. ...
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About a result of ms ssim

The above formula is from https://ieeexplore.ieee.org/document/1292216, the paper of ms-ssim. I calculated ms-ssim between two dummy images with this code: ...
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neural network for circle detection

I'm new to Neural Networks and I would appreciate any advice. I'm working with the raw data which can be visualized in the form of the image (32 pixels in the x direction and 128 pixels in the y ...
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3d object rotating from one given image

There is a game Stronghold 2001 with sprite graphics. Movable units in the game has different animations that consist of several frames. Each frame is usually represented by 8 sprites from different ...
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How to initialize k-means

I am working on image processing. I have to apply k-means upon them. But I am confused with the initialization of k-means that either I should use just first frame or all the frames to initialize it. ...
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How might disparity in image format/quality between binary classifications affect training of CNN?

I have an image dataset containing two classes. One of the classes has many images and they are all JPG images with the following format: ...
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Two image channels, one quantitative, one “relative”. Best architecture/preprocessing?

I'm performing semantic segmentation on a multi-channel image with a residual U-NET. I'm getting DICE scores that are ok for this task but I want to do even better. The problem is that the first ...
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Gaussian mixture model for image labelling task

I'm trying to solve an image labelling task by using Gaussian Mixture Models. The total number of classes in my dataset is 9, each representing a different variety of vegetable (Class1, Class2, Class3)...
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Machine learning algorithm to work with body keypoints from image

I'm working on a project that will predict whether a person approaches and intends to interact. There will be a camera and a pose estimation model that will analyze live frames and save the body parts ...
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standard deviation of two constant noised signals related through interpolation

Let us say say we have a noised constant signal and want to evaluate the standard deviation (std) of the noise. We calculate the std of the said noised signal and call it σ1. Now we process the signal,...
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What is a feature vector and how do they differ from feature maps

I'm reading a paper which reviews image upscaling techniques. A model named SRCNN is described as: First layer: creates feature maps from low-resolution input images Second layer: converts these ...
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Difference between Keras' DenseNet201, DenseNet169, and DenseNet121

I have been trying to use DenseNet architecture for the CIFAR-10 dataset. For the first trial I used DenseNet201, and got around 79% validation accuracy, which is pretty less than what I expected. So ...
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Encoding prior knowledge in image classification (A bayesian approach ?)

I have come across bayesian linear regression and bayesian logistic regression. These approaches sample from the posterior of the unknown parameters conditioned on the data using MCMC methods. The ...
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Difference in features generated by same filters for color and grayscale images?

Would there be ay difference between the features generated by CNNs if they are fed with same image in color and grayscale format. If I am performing classification with same network for let's say ...
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36 views

Using visual representation of time series of unequal length

I would like to apply methods like Gramian angular field, recurrence plots and Markov transition fields to a time series classification (TSC) problem where the time series themselves are all of ...
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Cross-validation necessary when using Random Forest?

I am new to this forum, but I am stuck with a couple questions related to image classification, and seeing the kind and highly useful messages that people provide, I had the hope that someone could ...
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Is there a “good” way to evaluate segmentation in weakly labeled image data?

I have an image dataset for anomaly detection, which has weakly labeled ground truth images for the anomalies. Therefore, if there is a defect in an image, the ground truth would have a relatively big ...
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Pytorch image recognition logistic regression - CIFAR-10 has flat loss curve (no improvement in accuracy after training)

Complete newbie to pytorch, Just started pytorch last week, but I've been dabbling in the theory and mathematics of machine learning for a few months, so I understand that part, mostly. I'm following ...
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Is it ok to organize the labels this way?

I'm a beginner with ML and I am trying to create models to classify whether an image from venus contains volcanoes using this dataset: https://www.kaggle.com/fmena14/volcanoesvenus The labels are ...
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Does it make sense to do VLAD encoding on top of features extracted with CNNs?

I have a deep learning framework which extracts features of patches of my images and builds a dictionary with PCA and then k-Means. Then the framework detects anomalies based on the distance of the ...
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Extract Features at Multiple Image-Scales

I try to replicate the results of this paper. They state, that they used VGG16- and VGG19-models pretrained on imagenet and used the output of the last convolutional layer (without relu and max-...
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Object detection vs segmentation?

My problem statement is as follows: "Object detection is the concept of classifiying & localising an object in an image, and semantic segmentation is the concept of labeling each pixel to a ...
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Interpreting the results of the paper of Kernalized correlation Filter KCF

Below is a snapshot of the output of the original paper of KCF.--> open link for full paper http://www.robots.ox.ac.uk/~joao/publications/henriques_eccv2012.pdf I have two questions: 1-in the ...
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Evaluate result of a Detection algorithm based on the object's shape as Ground truth

I'm working on project where i have to detect small colored cars driving on rails from static camera (Bird's Eye-view see below image) The algorithm in short outputs first a mask image with only the ...
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Pre- and post-feature extraction mutual information

My goal is to assess if, after applying a feature extraction method to images, I still have much in the extracted features to separate them into distinct classes. I start out being able to tell dogs ...
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1answer
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Scaling values to range -1 and 1 with large outliers

I have a set of images of size 64 x 64 with 3 color channels each. Each image contains a heat map (describing the browser usage). I'm scaling each pixel of this ...
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Resize image in object detection task of computer vision

In object detection, they usually resize by keeping the ratio the same as the original image, which usually names "letterbox" resize. My question is: Why we need to do that? As I see with ...
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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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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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23 views

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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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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