Abstract
In this paper, a new three-level thresholding method for image segmentation is proposed based on nonextensive entropy and fuzzy sets theory. Firstly, the image histogram is transformed from crisp set to fuzzy domain using fuzzy membership function, such as triangular membership function. After that, the nonextensive entropy of each part of fuzzy domain of histogram is computed. The threshold is selected by maximizing the nonextensive fuzzy entropy. However, the search of combination of membership function’s parameters is costly. For reduce the computation time, the artificial bee colony algorithm is used to search the optimal combination of the membership function’s parameters. The experimental results on tested images demonstrate the success of the proposed approach compared with the competing methods.
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