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In this study, segmentation of monochrome image into two classes (object and background) is performed by unsupervised classification method based on the hierarchical analysis of 2D-histograms. We perform the segmentation algorithm by reclassification of the pixels not classified in the determined classes according to Euclidean distance. The proposed approach has been tested on synthetic and real images...
Image segmentation algorithm based on fuzzy c-means clustering is an important algorithm in the image segmentation field. It has been used widely. However, it is not successfully to segment the noise image because the algorithm disregards of special constraint information. It only considers the gray information. Therefore, we proposed a weighed FCM algorithm based on Gaussian kernel function for image...
Classical gradient vector flow (GVF) based segmentation has been shown to work less well when other significant edges are present adjacent to the real boundary. To counter this, in this paper, we propose an improved energy function by consistently reducing the Euclidean distance between the inspected centroid of the real boundary and the estimated one of the snake. Experimental results show that our...
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