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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How to compare different data preprocessing when using CNN from sratch

Let's says you use a CNN for image classification. You have binary images: pixel values = 0 or 1. Some tools can be used to get those images with continuous values (i'll not explain how since that ...
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Intensity normalization with segmented ROI on black background

I have a set of segmented ROIs .jpgs against a black background. Pixels in the ROI range from 0 to 255 in grayscale (1 channel only). I want to normalize these intensities in order to feed it into a ...
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Does the TensorFlow object detection API understand the idea of “context”?

For example, if I'm creating an object detection model to recognize forms of transportation (cars, bikes, planes, etc.). If I also train it to recognize wheels, will it be more likely to detect wheels ...
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YOLO architecture clarifications

I am trying to train a YOLO model to draw bounding boxes around individual handwritten words. I don't need the network to classify them and I don't need the words to be in order either. I would have ...
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Can I train a CNN with a large number of input channels (more than 3, RGB)?

The input of the first layer would be composed of N channels and each input sample would look similar to this image (each plot is a channel) The label would be a number for each channel. The train/...
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Neural network to regress peaks in an image does not converge [duplicate]

I am trying to predict the position (x,y)-coordinates of 16 peaks in an image. The images look like the following: The green dots are the true peak locations and the red crosses represent a ...
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58 views

finding Human dimensions from photos

I'm working on a problem where I have to extract different human parts real-world dimensions ( waist width, arm length ) from photos where there are front and side photos, the given values are the ...
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Data balancing in image classification

I've to segment defects from an image. The image consists of only tomatoes with it's defects in it. The defects and tomatoes in the dataset are as follows: ...
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Finding objects in an entanglement

I'd like to know if there are ways to solve entanglement problems like this one: Given a known shape (in red), can a machine locate (or at least count) the instances of this same object in an image ...
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What are some line feature extraction tools?

I hope to find a feature extraction tool/method that specializes in extracting the features of a line, such as length, curvature, etc. Are there any such tools? The ones I found are image processing ...
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Strange results when computing the HOG and histogram intersection similarity

I am trying to re-implement algorithms mentioned in this paper to measure the "naturalness" of one synthetic image, given a real image. The algorithm seems straightforward, basically we have two ...
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variable number inputs to CNN

I am very new to deep learning and image recognition. Please let me know if my question needs more information. In the image recognition problem I am trying to solve, we are supposed to develop a ...
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Coming up with a metric that measures “homophily”?

[I'm not sure if this question goes here on Stats.SE --- please move if not.] Consider a 2D unit square. I observe N red and M blue balls on the square. I want to come up with a metric that measures ...
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18 views

Using one neural network for each image type

I have been reading about Convolutional neural networks and its use in image recognition. Most of the examples I have seen so far train one single network to classify an image into one label or class. ...
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Passing specific achors to YoLo training process

We are trying to improve our YoLo algorithm results of recognizing one class of varying sizes (~ varying distance to the camera). Luckily, the a priori position of the object is known with a certain ...
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CNN architectures for predicting next frame

I am currently trying to generate image of a body tissue at time t+1, by using image given at time t (or t-1,t-2...). Until now, I experimented on some Incomplete Conv Autoencoders in two main ...
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Stars and Machine Learning

Ok So I have been dying in interviews lately. Need to Brush up more. Maybe you can help me with this interview question (multiple Choice). If you tell me good sources to look at to learn more about ...
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Time complexity for locality sensitive hashing similar image search

I am trying to find most visually similar images for large image dataset. (N=1 million), using LSH (Locality Sensitive Hashing). Image feature vectors are 4096 dimensional VGG-16 features. Now, my ...
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Statistical Significance of a 3D Volume

I have two 3D volumes of a single patient. One 3D volume before surgery and one 3D volume after surgery. The 3D volumes are MRI images (Mangetic resonance imaging). Each 3D volume has dimensions [100, ...
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Increasing image size in pytorch celebrity generating GAN? [closed]

complete newbie here, bear with me. I'm making my way through this tutorial: https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html Upon attempting to make a simple change to the image ...
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What are the time complexity of image feature extraction algorithms, including HS, HOG, MSER and SIFT?

Can somebody help me by writing me a time-complexity of each image feature extraction algorithms. Especially I am interested in Harris-Stephens(HS) corner detection, Maximally Stable Extremal Regions (...
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Why is my keras resnet50 model overfitting? [duplicate]

I have applied Keras ResNet-50 on a small x-ray image dataset. I tried making layers both trainable and non-trainable, but my model validation accuracy doesn't improve above 50%. I don't understand ...
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How to reconstruct an image from a training set?

Description: I have taken a series of images/photos of a panorama from different positions (x,y) in space pretty close to each other (max 100m difference). Here there is a top view representation to ...
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Principal component analysis on RGB images

I've implemented a method to compute PCA on grayscale images. I haven't seen PCA on RGB images yet, which left me wondering if it is possible to perform it. With RGB images, is PCA done for each color ...
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Estimate Particle Density from Image Analysis

Suppose I have an old image of an object where the objective is to estimate the mean particle density of said object. Using a software called ImageJ, I am able to run a thresholding algorithm to ...
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An Interesting Model with Unknown Orthogonal Design Matrix

Consider a linear mixed model, $$\mathbf{y}_{ij}=\mathbf{\Gamma}\mathbf{\mu}+\mathbf{z}_i+\mathbf{e}_{ij}, ~~ ~~i=1,\ldots,m,~~j=1,\ldots,n_i, $$ where $\mathbf{y}_{ij}$ are $k\times 1$ observation ...
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What is the best way to normalise image data?

The normalisation in an image really confuses me. I mean there are multiple ways to do it (see below) but, is there the best one, or most preferable one, or one needs to experiment with all to find ...
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Does Sørensen–Dice Coefficient (Dice Score) only account for true positives?

I'm working in a project on medical image segmentation which uses the Dice Score as part of the loss function, but I got some doubts with the commonly adopted implementation. The definition of Dice ...
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Descriptive statistics for complementary random variables

I have two datasets, each one contains 157 images of microscopic field processed with a different preparation tecnique. My task is to show if there any differences like cells density, distribution and ...
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CNN, “squared” or "non-squared image?

I'm working on a project about image recognition. In my dataset I have images of different size, all rectangular image (the most 640x480 and 1280x640). I would like to build my classifier to ...
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How to solve MAP problem with images (EHT Bouman's Paper)

I'm not familiar with deep learning. Only know some basic concept about Neural Network. Recently I've tried to figure out the algorithm used to restore Black Hole image. After lot's of searching, I ...
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41 views

Particle filter for diagnosis

I have two annual measurements taken on medical images depicting a lung cancer tumor 's condition. I have likelihood function that taken in the measurement values and estimates malignancy of the tumor....
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Grad-CAM: Difference backprop modifier and grad modifier

I am using Grad-CAM to analyze my CNN. I want to apply a ReLU to the linear combination of feature maps because I am only interested in the features that have a positive influence on the class of ...
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How to find a threshold based on overlapping the histograms of two classes?

I want to perform thresholding to post-process the test data. I averaged the pixel intensity histograms of normal and abnormal cell images (grayscale, 8-bit, 256 * 256 images), overlapped them to ...
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CNN for image classification, new image representation as input

i'm trying to classify image pattern with CNN; I started to optimize a neural network with image represented in cartesian coordinate. If I use image represented in polar coordinate should i totaly ...
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67 views

Dealing with images of variable resolution in CNN autoencoders

Let's suppose would like to build a CNN autoencoder that would be able to turn greyscale images into coloured ones. The final model should be able to accept images of any resolution. Also, note that ...
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137 views

Calculate Earth Mover's Distance for two grayscale images

I am trying to calculate EMD (a.k.a. Wasserstein Distance) for these two grayscale (299x299) images/heatmaps: Right now, I am calculating the histogram/distribution of both images. The histograms ...
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101 views

Eigenvalues as weighting factors for projection results on corresponding eigenvectors in PCA

In the paper Novel PCA-based Color-to-gray Image Conversion, the authors project the three-dimensional $(R, G, B)$ value of each pixel onto a one-dimensional grayscale space via a curious application ...
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64 views

Statistically compare similarity between images

I have two images/heatmaps (2d matrix) of identical size. I need to statistically compare the similarity between the two. With 'similarity', I mean that high and low values of one image appear in ...
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What is sigma function in the YOLO object detector?

I have gone through the YOLO9000 paper, in that they have mentioned that network predicts 5 coordinates of the bounding box, and from that we find the exact centre coordinates and the width and height....
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Detecting trend in panel data, smoothing techniques and outlier detection

I'm conducting an analysis on a Landsat scene to detect trends for change detection phenomena (forest disturbances) over a time series of 20 years. I identified on the image the pixels that are ...
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What are the important methods that evolved in computing optical flow?

I have gone through various approaches to find optical flow. But I have a tad confusion between Horn and Shunck method and Lucas Kannede method. Where are these methods useful and where do these ...
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Is it feasible to train a model from scratch using 10000 images

Hi Everyone I am a beginner in deep learning and doing a project on deep learning for my college. I want to train a CNN that can classify three classes of Skin Cancer namely Melanoma, Sebborhic ...
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Handle loss while converting high dimensional image to specific size in VGG 16

I am training a VGG16 net using transfer learning. I have removed the fully connected layers and used fine tuning to classify objects into few categories but I have faced below problems: 1.I have ...
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What is scale-invariance and log-space translations of a bounding box?

In slow R-CNN paper, the bounding box regression's goal is to learn a transformation that maps a proposed bounding box P to a ground-truth box G and we parameterize the transformation in terms of four ...
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Augmentation of data collected from single stationary source

How do one augment data that is being collected from single stationary sensor source. The orientation, color and size always remain same. Only the pattern in the dataset vary (example : sunspots are ...
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43 views

How can K-Means clustering work without spatial information?

Just got stuck at working with K-means clustering. I have looked up this python/skimage commands: ...
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Audio files and their corresponding spectrograms for image classification process

Suppose I have a dataset of audio files that I have to use for whale sound classification. I am choosing the strategy of treating it as an image classification problem by using their corresponding ...
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Is background subtraction common practice for image classification?

I am going to build a mushroom identification application and using neural networks for image classification. Right now I am thinking about different image processing methods to implement before ...
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How do backbone and head architecture work in Mask R-CNN?

In this diagram, we see the two convs. It is said that these convs are a part of the Fully Convolution Network (FCN). In their paper Mask R-CNN (He et al., 2018), they mentioned something about the ...