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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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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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Feedback regarding dependability of duplicate and near-duplicate detection [on hold]

Good morning all, I recently completed building a script that does the following: Stores a list of all .jpg images existing in specified drive. Cleans/ids duplicates through md5sum Iterates through ...
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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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Models for document segmentation

I have been tasked with writing an algorithm which can segment a PDF-document, or an image of said document, into segments of text, tables or image. However, I am not sure which models to use. It ...
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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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38 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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1answer
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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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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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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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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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1answer
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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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2answers
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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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1answer
26 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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23 views

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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1answer
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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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1answer
166 views

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 ...
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What is the best image labelling tool with these features?

I need an image labeling tool that has the following features: Upload images on the fly (via API or something) I want to compare specific pairs of images, and indicate if they are the same, or not ...
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modelling an image matrix with correlated pixel values

Trying to improve a certain algorithm for manipulating certain micrograph images, I would like to experiment with "random" synthetic images as input to the algorithm. The pixel entries would be non-...
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How to ensemble predictions from image classifier and text classifier?

I am doing multiclass classification based on images and text. I have predictions from both image classification and text. I am not sure how to combine them. Should I use probabilities as a feature to ...
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How to reproduce this algorithm?

I am trying to reproduce one of the algorithms presented in the following paper: Rapid Assessment of Annual Deforestation in the Brazilian Amazon Using MODIS Data The authors provide five different ...
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68 views

Image classification with large images

I am new to image classification and hope to set up a model which will classify large images (I am using R keras). Each image will represent a 10m by 10m square with pixels representing 1 cm. I need ...
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1answer
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Per-pixel classification using deep learning models

I want to train a model to classify image pixels in which neighbouring pixels are not considered, only channels (bands) for each pixel. I'm thinking about defining a CNN model which stacks several ...
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Basis vectors for categorical images

I have a sequence of categorical images. For a two category image, each image pixel can have one of two values. I would like to analyze these images using a technique like eigen images. The goal is to ...
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Stereo image classification [closed]

I just been wondering how can I combine stereo vision and Convolutional neural networks for a classification problem
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2answers
191 views

Generating vector image from a hand drawn picture. Machine Learning

I am new to machine learning! I need a way to generate vector image out of hand drawn sketch. I dont need to trace bitmap like it is usally done because it gives you exactly what you drawn. I need to ...
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1answer
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Dimensions and implementation of the Convolution step in CNN

I am trying to write my own convolutional neural network from scratch (Python) and after reading several articles and watching tutorials (on CNN) there are still a couple of issues that I am unable to ...
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1answer
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How we determine the ground truth box of the object in each frame in Matlab?

When we track one object in a video sequence using a tracking object method, the estimated bounding box is given by the method for every frame of the video. But how we determine the ground truth box ...
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1answer
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Statistical Reasoning of Noise Images on Random Pixel Generator

http://www.pixelmonkeys.org/#theory It is always explained that even billions of images are generated per second, it is almost impossible to see a natural image ( whether it is clear or distorted as ...
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2answers
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Object Localisation without Classification

I have a data set of photos containing an object in each of them. I want to find out the coordinates of rectangle enclosing the object. Note that each photo contains exactly 1 object (for example, if ...
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1answer
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How do ConvNets self-organise to have a hierarchical segmentation of higher- and lower-level features?

As far as I know, each layer of a convolutional neural network used for image classification specializes in recognizing a different part of an image. At earlier stages in the network, more rudimentary ...
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1answer
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Image Augmentation or incrementing dataset by flipping/mirroring?

My task is a regression task, where an input image results in another, transformed image. So far so good, works quite well. As my data set is fairly small, I want to take some actions. Here I wanted ...
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1answer
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Which machine learning approach to use for data with very low variability and a small training set?

My goal is to write a program which recognizes the chess position in an image of a digital game. I'm not trying to process actual photos of a game in real life, just images like the own below This ...
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1answer
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image caption generator

I see two models of image caption generator online: In the above model, the first LSTM cell of decoder takes the entire image as an input. In the above model, all the LSTM cells of the decoder take ...
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Future of statistical methods in image segmentation? [closed]

I was looking for a purely statistical method for image segmentation and found many, e.g. Hidden Markov Random Fields with EM algorithm. But it seems to me that these methods are nowadays completely ...