Image segmentation classifies an image into regions using k-means clustering. First, partial stretching enhances image quality, and subtractive clustering determines initial centroids. K-means then segments the image, followed by a median filter to remove noise, resulting in clear and precise regions of interest.
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Image segmentation classifies an image into regions using k-means clustering. First, partial stretching enhances image quality, and subtractive clustering determines initial centroids. K-means then segments the image, followed by a median filter to remove noise, resulting in clear and precise regions of interest.
sharanya-dasgupta001/Image-Segmentation-using-K-means-Clustering-Algorithm-and-Subtractive-Clustering-Algorithm
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Image segmentation classifies an image into regions using k-means clustering. First, partial stretching enhances image quality, and subtractive clustering determines initial centroids. K-means then segments the image, followed by a median filter to remove noise, resulting in clear and precise regions of interest.
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