@article {880,
	title = {A novel image thresholding method based on membrane computing and fuzzy entropy},
	journal = {Journal of Intelligent and Fuzzy Systems},
	volume = {2},
	year = {2013},
	pages = {229-237},
	publisher = {IOS Press},
	edition = {24},
	address = {Amsterdam, Netherlands},
	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.},
	keywords = {fuzzy entropy, Image segmentation, Membrane computing, thresholding method, Tissue P Systems},
	issn = {1064-1246},
	doi = {10.3233/IFS-2012-0549},
	url = {http://iospress.metapress.com/content/j542m5p0048588g2/?p=ea45f12cd9f04dd4815022f7d89cf1f8\&pi=14},
	author = {Hong Peng and Jun Wang and Mario J. P{\'e}rez-Jim{\'e}nez and Peng Shi}
}
