A novel image thresholding method based on membrane computing and fuzzy entropy
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)
Abstract
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 | 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 | 66 - View on Scopus |
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