A novel image thresholding method based on membrane computing and fuzzy entropy

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Peng, Hong, Wang, June, Pérez-Jiménez, Mario J and Shi, Peng (2012) A novel image thresholding method based on membrane computing and fuzzy entropy. Journal of Intelligent and Fuzzy Systems, 24 (2). pp. 229-237. ISSN 1064-1246 (print) 1875-8967 (online)


Multi-level thresholding methods are a class of most popular image segmentation techniques, however, they are not computationally efficient since they exhaustively search the optimal thresholds to optimize the objective function. In order to eliminate the shortcoming, a novel multi-level thresholding method for image segmentation based on tissue P systems is proposed in this paper. The fuzzy entropy is used as the evaluation criterion to find optimal segmentation thresholds. The presented method can effectively search the optimal thresholds for multi-level thresholding based on fuzzy entropy due to parallel computing ability and particular mechanism of tissue P systems. Experimental results of both qualitative and quantitative comparisons for the proposed method and several existing methods illustrate its applicability and effectiveness.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/23939
DOI https://doi.org/10.3233/IFS-2012-0549
Official URL http://iospress.metapress.com/content/j542m5p00485...
Subjects Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing
Current > Division/Research > College of Science and Engineering
Keywords ResPubID26694, image segmentation, thresholding method, membrane computing, tissue P systems, fuzzy entropy
Citations in Scopus 64 - View on Scopus
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