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Image Segmentation based on an Iterative Computation of the Mean Shift Filtering for different values of window sizes

Roberto Rodríguez, Esley Torres, Juan H. Sossa


Image segmentation is recognized to be one of the most important steps in most high-level image analysis systems. Its precise functioning highly determines the performance of the entire system. For years the most robust segmentation algorithms have been the iterative methods, which have covered a variety of techniques. In this paper, we have researched the performance of a segmentation algorithm that uses an iterative computation of the mean shift filtering by using different window sizes. All the experimentation was done with standard images. A comparison of the obtained results was carried out with the different window sizes, as for the degree of homogenization of the segmented images as the number of iterations.


Entropy, image segmentation, mean shift, algorithm, window sizes

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