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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37 views

What it mean by Training SVM

I am new to image processing. As my project I am doing "image classifier using SVM". I have the idea of my final software "I select some image and give it as input to my software and it will classify ...
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14 views

Looking for a CNN implementation for 3D images

I'm looking for an implementation in python (or eventually matlab) of Convolutional Neural Networks for 3D images. By 3D I mean 3 spatial dimensions (i.e. not 2D+channels or 2D+time). Any advice?
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21 views

How to compute dense depth map from DAISY Descriptors?

The paper, "DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo" by Tola et al. , describes a fast local descriptor called DAISY which is used to estimate dense depth map from ...
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22 views

Time series and images : difference and terminology

A time series is an ordered collection of random variables. Considering a one-dimensional time series $A_i = {a_{i1},a_{i2},\ldots,a_{it}}$ where $t$ denotes the time index. So, the time series is a ...
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1answer
29 views

Need guidance on image classification problem with large feature matrix

So I've got an interesting problem that I'm struggling with and I wanted to hear some ideas on possible solutions. The data is not public and I can't go into much detail. The problem involves a ...
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0answers
10 views

Detect bounding box of tables in PDF page

I am new to Machine Learning, doing courses and reading papers, and would like to solve the following problem as my learning journey: Given a PDF page I would like to detect the bounding boxes of all ...
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0answers
45 views

find outlier in 1D array

I have a satellite images, which have none values (which are not all equal to 0) on right and left side of an image and it is not a strait line. I would liked to write a program, which finds the ...
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0answers
15 views

CNN localizing object?

For classying images/objects CNNs are one possible or even the state-of-the-art solution but what if one wants to localize an object in an image? I thought if I use only convolutional layers without ...
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0answers
25 views

Help: Random Forest optimization (image classification)

I'm having trouble classifying images using a random forest. The images all have a very similar scale, but they may be rotated arbitrarily around a fixed point in the image. The core problem is ...
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0answers
10 views

how can use otsu's method?

I want to do binarization on my images. if my images have Intensity homogeneities, it means that they don't have local variation in both background and foreground I can use global thresholding. I ...
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0answers
32 views

Image recognition fails when given image not in training set

I am a beginner in Neural network. What I am trying to implement is an image recognizing tool. Neuroph Studio was used for training and creating the trained data set. A set of images of cars were ...
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0answers
12 views

Shifting input over image for CNN object detection?

I've got a CNN which is trained supervised and calculates if a specific object is present in an image. Since I am interested in the object's position in the image I tried to alter my architecture so ...
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1answer
40 views

How to prepare colored images for neural networks?

I have seen many examples online regarding the MNIST dataset, but it's all in black and white. In that case, a 2D array can be constructed where the values at each array element represent the ...
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0answers
70 views

Neural Network for Image Recognition fails to converge

I have implemented a MLP neural network, which is being used to recognise human faces. The NN's input layer has 175 neurons which represent an image (25x25 dimensions), the data for each image is ...
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1answer
27 views

Recognition of digit of size other than those in the training set using DNNs

I have a DNN trained on MNIST data (image 1 for digit '4') that recognizes images from the test set with high precision. Each digit is centered and all of them are roughly of the equal size. Will it ...
3
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2answers
74 views

Theoretical justification for bag of words

Bag of words and visual bag of words are successful machine learning approaches. Does anyone know of a theoretical justification for why / when they work? What I am trying to explain is the good ...
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0answers
7 views

What are state-of-the art scanned page segmentation techniques?

I am interested in extracting images from scanned book pages. I assume this is something Google would do for their image search, since they have scanned millions of books. After a quick look at the ...
2
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1answer
38 views

Why do we need to normalize the images before we put them into CNN?

I am not clear the reason that we normalise the image for CNN by (image - mean_image)? Thanks!
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0answers
23 views

What are good / simple techniques available for segmenting non-cursive handwriting images?

I need to process English hand-written form fields. So the hand-writings are expected to be mostly non-cursive but the letters may occasionally overlap with each other slightly, with some punctuation ...
2
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0answers
93 views

Comparing two histograms using Chi-Square distance

I want to compare two images of faces. I calculated their LBP-histograms. So now I need to compare these two histograms and get something that will tell how much these histograms are equal (0 - 100%). ...
2
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0answers
126 views

Recurrent neural network for object tracking & position filtering?

Would a recurrent neural network be appropriate for object tracking tasks? Mainly I will have 3D feature vectors $(x, y, t)$ where $x$ and $y$ are the positions of an object in the image and $t$ is ...
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1answer
60 views

Advantage of latent SVM for part-based object detection

In the famous paper Object Detection with Discriminatively Trained Part Based Models, the authors use a Latent SVM approach to learn the detector of each part, because the localization of the parts in ...
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1answer
34 views

Sensitivity of DNN-based classifiers to centering and orientation of object in images

Is DNN classification senstitive to centering and orientation of object in images? for instance: Let us assume that a DNN is trained with letters always appearing in the same given orientation (e.g. ...
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0answers
17 views

Uncertainty in pixel intensity value due to the spatial uncertainty of phenomena

Assume we have image of point object (I use Gaussian PSF). Let's assume that position of this point object is not precisely known due to some phenomena. Spatial position of point source can be ...
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1answer
60 views

How do I compute a realization of h(x) given its PDF and covariance?

I've added a picture of what I want to compute. In the nomenclature of the picture, I want to compute a realization of y(x) given the known distributions and constants. Let's say y(x), random ...
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1answer
83 views

Feature detection from satellite images

I'm having a couple of thousand clear satellite pictures and would like to extract features out of them, like outdoor swimming pools, solar panels, presence of green space, ... I was wondering if ...
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2answers
72 views

Data augmentation step in Krizhevsky et al. paper

In the paper Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012., ...
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38 views

CRF or MRF energy functions for image segmentation

I am currently working on image segmentation for the purposes of computer vision. I have read many papers and a few books dealing with MRFs and CRFs for computer vision. All of them define an energy ...
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0answers
23 views

DeepLearning layer construction good at detection certain patterns?

I am kinda new to the deep learning field, but hope some of you could be helpful clarifying some things.. I am using the Caffe library to create a caffemodel, capable of distinguish the ...
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0answers
53 views

Cost function for image segmentation

I am currently working on image segmentation based on superpixels. My input is a data matrix that contains stixels (rectangular superpixels that span an entire column). In the matrix I have stixel ID, ...
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1answer
41 views

Approaches used for defining deep layers?

I am at the moment trying to build an image classifier, capable of determining if an image contains an object X. To do this I have been thinking of using deep learning, to make the system more ...
3
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0answers
72 views

CNN - Extract visual information via Gradient Descent with Backpropagation

I'm trying to reproduce the results from this paper: Mahendran, Aravindh, and Andrea Vedaldi. "Understanding deep image representations by inverting them." arXiv preprint arXiv:1412.0035 (2014). One ...
2
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0answers
44 views

Separation of points clouds via classification methods

I have multiple images from a 3D-Scanner in point cloud form. Part of the image is a fixture to hold the object to be scanned. I want to extract the object itself by classifying the fixture and the ...
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1answer
20 views

Finding object in the image

I'm working on building a classifier that needs to find one particular object in the photo. I'm planning on using SIFT/SURF + kmeans for feature extraction and logistic regression for classification. ...
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0answers
72 views

Model for supervised learning on graphs with varying structure

Colorization problem is considered. I have a training set of unordered graphs (images) with varying number of vertices and edges (color regions and adjacency between them, resp.). A fixed number ...
2
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1answer
44 views

Singular value decomposition on RGB images

Is singular value decomposition (SVD) only done for grayscale images? All examples in the literature seem to focus on grayscale images. I was wondering if SVD also makes sense if applied to each of ...
3
votes
1answer
79 views

Identify region of interest in image

I'm currently trying to work on the challenge https://www.kaggle.com/c/noaa-right-whale-recognition; I've done basic image recognition work before (Identifying plankton), but this particular challenge ...
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0answers
13 views

Leakage between training examples possible?

I have the following situation and I'm not sure if it classifies as leakage or not. Any insight would be highly appreciated. In my training set I have a number of images in the form of gray-level ...
1
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1answer
40 views

Detect multiple classes in an image?

I have a deep neural network trained with data of different kinds of fruits (apples, oranges, guava, pear, etc.). In my testing data, I have multiple fruits in the same image. For example, an image ...
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2answers
54 views

Automatic background removal from images without user interaction

I am trying to develop an image search application. I have crawled through e-commerce websites and obtained a data set of images (about 2.5 Million). Now I want to identify the object of interest from ...
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0answers
22 views

How can I get the sqrt of a matrix in Theano

To clarify, I don't want to find the sqrt element wise which I can do T.sqrt(some_matrix). I'm trying to do whitening transforms as shown here: x˜ = ED−1/2E T x ...
2
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0answers
17 views

How many samples do I need for OCR problems?

I am thinking about collecting samples of hand written digits (0 to 9) from people. I'll try to test different algorithms for optimal character recognition- some form of neural network and random ...
1
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0answers
23 views

Suggested books/readings on spatial statistics for remote sensing

I'm taking a class on statistics for image analysis and I'm thinking of getting some background reading on the subject. Anybody know a good book/website/readings on the subject? I'm coming from a ...
0
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0answers
32 views

neural network for 3D pictures

I'm wondering if they are some state-of-art algorithms to apply the convolutional neural network approach to 3D pictures, eg. input is no longer a grid of pixels, but voxels. My objective is to ...
0
votes
1answer
66 views

featurizing images of different sizes

I'm training a non linear svm to do classification on images. I'm featurizing the image by creating 3 features for each pixel, its rgb value. My question is: How should i normalize images of different ...
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0answers
26 views

How to construct 3D image from 2D image using Markov Random Field?

I have one 2D CT image and I want to convert it to 3D image using Markov Random Field. There are several papers in the literature in which this technique was used based on 3 2D orthogonal images. ...
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0answers
33 views

What Percent of Neural Network is used while processing a single image

What percent (on average) of entire Neural network (say, AlexNet) is actually used while processing a single image. There should only a very small amount of network that should actually be utilized ...
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0answers
25 views

Math behind alpha calculation in matting

As we know for matting, Iz = αzFz + (1 − αz)Bz where, Iz is the observed pixel color (a 3d vector in rgb, say) αz is a scalar value ranging between 0 and 1 Fz,Bz are the (estimated) values of ...
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0answers
56 views

Suitable statistical test for comparing pixel intensity between multiple images

I have a series of 3D images derived from CT scans. They have all been transformed so that all homologous features should be in the same relative position. I would like to find out, at each pixel ...
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1answer
377 views

Need guidance in image classification

I'm new to machine learning and need some help. I need image classification to tell if an image is a car or not. Is there any working example or guidance or a book for this particular question? ...