Abstract
This paper proposes an image thresholding segmentation method, which combines tissue membrane systems and velocity-position model. A tissue membrane system is used as its computing framework and an improved velocity-position model is integrated as evolution rules of objects in cells. Due to parallel computing ability and inherent evolution-communication mechanism of the tissue membrane system, the presented hybrid method can effectively and efficiently find the optimal thresholds for three-level thresholding based on total fuzzy entropy. The performance of the presented hybrid method is studied with several evolutionary algorithms. Simulation results show that the presented hybrid method is superior or comparable to the other evolutionary algorithms and can be efficiently used for image thresholding. Keywordsimage thresholding; membrane computing; tissue membrane systems; total fuzzy entropy
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