Abstract
In image processing, one of the most efficient techniques for image segmentation is entropy-based thresholding. In this work a generalized entropy formalism that represents a recent development in statistical mechanics was applied. We propose, for the first time, an image thresholding method using a nonextensive entropy regarding the presence of nonadditive information content in image classes. Preliminary results are shown.
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