# Tag Info

### Best way of segmenting veins in leaves?

Following on from the above excellent answer, here is how to do it in python using scikit funcitons. ...

### How to Calculate the Local Gradient of an Image in MATLAB

First of all, pay attention it is a calculation per pixel using a sata from a blog. Basically summing the Gradient norm over a block / windows. To calculate what you submitted above do the following: ...
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### How do we distinguish between Image Recognition,Detection and Segmentation?

It can be a little confusing at times, and the terms are not completely independent. Detection: In detection, you are simply detection the presence of something. For example, you might design an ...

### How to Use Maximum a Posteriori Probability (MAP) in Classification Task

I will try to give you some intuition into it by a different example. Think we have 3 machines which can generate the numbers 1, 2, 3. The first machine generates the number 1 with 80% and the ...

### Best way of segmenting veins from arm?

So one good step to enhance the vein-like structures is coherence enhancing diffusion: Weickert, Joachim. "Coherence-enhancing diffusion filtering." International Journal of Computer Vision 31.2-3 (...
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### Should Edge Detection Be Applied in Spatial or in Frequency Domain?

We need to separate the concept of edge detection from the tools we use to apply the procedure. Edges are local property of the image. Being so local means we don't analyze the image in frequency ...

### Matlab - Segment cell nucleus from similar background

You need to work with different color space. Try YCbCr for instance ...
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### How to Cluster Image Colors Using K Means Clustering in CIE a*b Domain?

You should use makecform to create a color transfer structure. You should use srgb2lab to create a structure which will convert ...

### How to Detect a Inhomogeneity Region in Image

There are many properties of inhomogeneity: Local Variance / STD. Local Histogram. The Gradient Function Histogram of the Gradient. Mean versus the Median / Mode.
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### K-means for 2D point clustering in python

It can be done very easily with the scikit-learn. Examples are easy to find on their website, i.e. here. In my opinion it is the best way to go. Modified code example from the above link: ...

### Denoise Image with Gaussian Noise Using MATLAB / Octave

You're trying to solve what's called Perona Malik Non Linear Diffusion Problem (Sometimes people call it, by mistake, Anisotropic Diffusion). Anyhow, the simplest code for that is Anisotropic ...
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### Which method to remove small unwanted region and fill holes

This code work fine for me. You try ...

### How Do I Plot Color Distribution of HSV Image in MATLAB

Have a look at File Exchange Submission - RGB/HSV Distribution on visualization of RGB/HSV distribution in a given image: hsv_distribution(inputImage, 5) It ...

### Comparison Between Average Kernel (Box Kernel) and Gaussian Kernel

If you pre calculate the filter coefficients the complexity of the convolution is set by its radius only. Yet, if all coefficients are the same, it could be reduced into summation and one ...
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### What Is "Description Vector" in Image Processing?

I think you have a matrix. Each Row / Column is a descriptor vector of a point in the image. Just like having features, let's say M features, and each point has M values corresponding to M features. ...
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### Detect circles in image

1) Normalize your image to range $[0,255]$. 2) Select a threshold and threshold the image. For your image, what worked is: $\tau=[140-150]$. 3) Compute a Euclidean distance transform. 4) Apply ...
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### How to Remove the Patch Artifacts of Neural Network Denoising Process?

One simple way to solve it is using Overlapping Patches. Let's say you have image which is $20 \times 20$ and you work on patches of the size $5 \times 5$. As I understand from your description ...
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### Is HSV Color Space Sufficient for Rudimentary Color ID and Edge Detection

The approach seems reasonable. Indeed doing edge detection in weighted RGB channel is the classic approach (Though you could also employ more advance methods, See Edge Detection on a Color Image). I ...
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### Algorithm that Fills the White Holes Within the Character Image

Based on the blog post - The Paint Bucket in Paint.Net 4.0 (Video) I can tell it uses some edge detection to handle similar colors within a piece wise smooth area. More information is given in the ...

### Easiest Pattern to Recognize with Machine Vision

In case you can shoot a video of the static scene than a blinking light would be the easiest as you could easily detect it by subtracting the n - 1 frame from the <...
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### What is Label Refinement in the Context of Image Segmentation

The correct context of the refinement key word is segmentation. Label Refinement in the context of image segmentation is a step to increase the resolution and understanding of the segmentation. It can ...
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### Locate Non Homogenous Areas in an Image

In general, the approach to take, is to have a local feature which has high value for such areas in the image. There are many approaches to shape such a feature. Probably the easiest one would be by ...
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### Image Segmentation Using Deep Learning

Well, I think the best way to tackle this question is a little background and a code as an example. I chose MATLAB for this example though PyTorch / Keras would probably be as easy. This task requires ...
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### Rectangle Segments of Image (Rectangle Super Pixels) per Pixel

One answer for your question would be limiting Super Pixels to rectangle forms. It requires changing the code of a Super Pixel algorithm to constraint the shape of the Super Pixel. Another approach ...
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### Dynamic Textures

A dynamic texture is a texture that is a function of space and time. In Image Synthesis papers, it is a term often used to designate things like: a flame, a waving flag, specular reflections on water....
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### Deriving the Euler-Lagrange Equations for the Chan-Vese Model

Thanks to Luminita Vese, who responded to this question via email. I will post the answer here. Let $\varphi_\epsilon(x) = \varphi(x) + \epsilon\eta(x)$ for some test function $\eta(x)$. \begin{...
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### What Is the Difference Between MRF and Total Variation in Noise Removal?

These are two different concepts that you talk about. First, MRF gives you a framework to do discrete optimization of problems, which respect the Markovian property, that is a pixel is conditioned ...