College of Computer and Information Technology, Henan Normal University, Xinxiang 453007, China

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Abstract—The two-dimensional (2-D) maximum Tsallis entropy method often gets ideal segmentation results, because it not only takes advantage of the spatial neighbor information with using the 2-D histogram of the image, but also has some flexibility with a parameter. However, its time-consuming computation is often an obstacle in real time application systems. In this paper, a fast image thresholding method based on chaos optimization and recursive algorithm for 2-D Tsallis entropy is presented. Firstly, improve the traditional chaos optimization algorithm(COA) so that it can get global solution with lower computation load, then propose a recursive algorithm with the stored matrix variables, finally combine the improved COA and the recursive algorithm to reduce much computational cost in the process of solving the 2-D maximum Tsallis entropy problem. Experimental results show the proposed approach can get better segmentation performance and has much faster speed.

Index Terms—Image thresholding, Two-dimensional (2-D) Tsallis entropy, Chaos optimization algorithm (COA), Recursive algorithm

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Cite: Xinming Zhang and Lin Yan, " A Fast Image Thresholding Method Based on Chaos Optimization and Recursive Algorithm for Two- Dimensional Tsallis Entropy," Journal of Computers vol. 5, no. 7, pp. 1054-1061, 2010.