Image segmentation using gaussian mixture model clustering based on the blobworld paper
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I'm new to machine learning implementation and I'm trying to implement the image segmentation approach from the Blobworld paper. I have extracted the 6 feature vectors of the image that are described in the paper and I have them saved in matrix X which has 6 rows that are each a feature and number of pixels from the input image as columns.
I have managed to write the code that extracts the features. and now I need to cluster the feature vectors into gaussian clusters using EM:
X = double(computeBlobworldFeatureVectors(original_image));%original_image is the image from imread('zebra.jpg'); same image from the paper
X = X([1 2 3 6 5 4], :);%l*,a*,b*,contrast,anistropy,polarity
I am now trying to do (d) from the following image that is snapped from the paper :
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Asvin Kumar
2020 年 6 月 8 日
Here's a popular implementation of the EM algorithm from File Exchange which might be of use to you:
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This is one of the several submissions in MATLAB File Exchange on MATLAB Central which is a forum for our product users to interact, exchange information and knowledge, without MathWorks' involvement. Feel free to contact the author of this submission directly for specific questions about the implementation
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