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Research On Automatic Image Segmentation Algorithm Based On Improved FCM

Posted on:2016-04-01Degree:MasterType:Thesis
Country:ChinaCandidate:Y G ZhaoFull Text:PDF
GTID:2348330482479705Subject:Software engineering
Abstract/Summary:PDF Full Text Request
Because fuzzy C-means algorithm (FCM) can not automatically determine the cluster centers, and doesn't consider the neighborhood pixels' information, a new automatic image segmentation method is proposed based on improved FCM. The cluster number of the image is obtained by image histogram. And the initial cluster centers are obtained by using an improved fast FCM method. That is, they are obtained by using one step k-means algorithm for large membership degree gray values and only updating the small membership values using fast FCM. It iterates to obtain the initial cluster centers. Image segmentation can be done by using improved membership FCM algorithm. Experiments show that this method generates a closer initial cluster center values to the final clustering centers, reduces the computing time, and has stronger anti-noise property.
Keywords/Search Tags:k-means, fuzzy c-means, image segmentation, neighborhood information, automatic image segmentation
PDF Full Text Request
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