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Skin lesion detection for digital image using tdls algorithm

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Adama07

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Skin lesion detection in digital image

Hi

I'm trying to implement skin lesion detections as ùelanoma.

I want to implement "Texture Distinctiveness Lesion Segmentation (TDLS) Algorithm" in MATLAB.

Is anybody work on it?
 

Hi,

I'm trying to implement skin lesion detections as melanoma using "Texture Distinctiveness Lesion Segmentation (TDLS) Algorithm" in MATLAB.

*** step 1, 2 & 3 of TDLS***

Convert the corrected image to the XYZ color space.
* XYZ is not RGB, but approximately equal to RGB color space.

Learn the sparse texture model.
* For each pixel s in image I, extract the texture vector to obtain the set of texture vectors T.
? = { ??? |1 ≤ ? ≤ ? × ? }
* A set of N x M texture vectors extracted. (N x M – pixel size)

Cluster the texture vectors in T, using k-means clustering algorithm, to obtain the representative texture distributions.
1. K-means clustering algorithm.



Ck – kth set of texture vectors, μk – mean vector of kth set.
* Find K clusters that minimizes the sum of squared error between cluster members tsj
and cluster mean μk.


****** that is what I code for step 1 & 2 but I'm not sure ****

[syntax=scilab] I=imread('1.jpg'); imD=double(Im); imC = rgb2xyz(imD); s=size(imC); imR=reshape(imC,numel(imC)/3,3); [idx, C] = kmeans(ImR, K,'Display', 'final'); S = zeros( size(ImR) ); for i = 1:K idg = find((idx == i)); S(idg,:) = repmat(C(i,:),size(idg,1),1); end S = reshape(S,N,M,3); figure(45); imshow((S)); title('Image Clustered')[/syntax]

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I wanted to know if reshape does "extract the texture vector for each pixel in the image"

Thanks in adavance
 
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