Image Thresholding with Cell-like P Systems

P systems are a new class of distributed parallel computing models. In this paper, a novel three-level thresholding approach for image segmentation based on celllike P systems is proposed in order to improve the computational efficiency of multilevel thresholding. A cell-like P system with a specially designed membrane structure is developed and an improved evolution mechanism is integrated into the cell-like P system. Due to parallel computing ability and particular mechanism of the cell-like P system, the presented thresholding approach can effectively search the optimal thresholds for threelevel thresholding based on total fuzzy entropy. Experimental results of both qualitative and quantitative comparisons for the proposed approach and GA-based and PSO-based approaches illustrate the applicability and effectiveness.

[1]  Mario J Pérez-Jiménez,et al.  Membrane computing: brief introduction, recent results and applications. , 2006, Bio Systems.

[2]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[3]  Peng-Yeng Yin,et al.  A fast scheme for optimal thresholding using genetic algorithms , 1999, Signal Process..

[4]  Mao-Jiun J. Wang,et al.  Image thresholding by minimizing the measures of fuzzines , 1995, Pattern Recognit..

[5]  H. D. Cheng,et al.  Thresholding using two-dimensional histogram and fuzzy entropy principle , 2000, IEEE Trans. Image Process..

[6]  Gheorghe Paun.  Spiking Neural P Systems: A Tutorial , 2007, Bull. EATCS.

[7]  Pau-Choo Chung,et al.  A Fast Algorithm for Multilevel Thresholding , 2001, J. Inf. Sci. Eng..

[8]  Dong Liu,et al.  A novel fuzzy classification entropy approach to image thresholding , 2006, Pattern Recognit. Lett..

[9]  Pedro Real Jurado,et al.  A cellular Way to Obtain Homology Groups in Binary 2D Images , 2010 .

[10]  Gabriel Ciobanu,et al.  Distributed Evolutionary Algorithms Inspired by Membranes in Solving Continuous Optimization Problems , 2006, Workshop on Membrane Computing.

[11]  Andrew K. C. Wong,et al.  A new method for gray-level picture thresholding using the entropy of the histogram , 1985, Comput. Vis. Graph. Image Process..

[12]  B. Kulkarni,et al.  An ant colony approach for clustering , 2004 .

[13]  Rudolf Freund,et al.  Tissue-like P Systems with Channel-States , 2004 .

[14]  Patrick Siarry,et al.  A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation , 2008, Comput. Vis. Image Underst..

[15]  Ying Sun,et al.  A novel fuzzy entropy approach to image enhancement and thresholding , 1999, Signal Process..

[16]  Hong Yan,et al.  A technique of three-level thresholding based on probability partition and fuzzy 3-partition , 2001, IEEE Trans. Fuzzy Syst..

[17]  Hao Gao,et al.  Multilevel Thresholding for Image Segmentation Through an Improved Quantum-Behaved Particle Swarm Algorithm , 2010, IEEE Transactions on Instrumentation and Measurement.

[18]  Hai Jin,et al.  Object segmentation using ant colony optimization algorithm and fuzzy entropy , 2007, Pattern Recognit. Lett..

[19]  Hong Peng,et al.  AN EXTENDED SPIKING NEURAL P SYSTEM FOR FUZZY KNOWLEDGE REPRESENTATION , 2011 .

[20]  P.K Sahoo,et al.  A survey of thresholding techniques , 1988, Comput. Vis. Graph. Image Process..

[21]  Gheorghe Paun,et al.  Computing with Membranes , 2000, J. Comput. Syst. Sci..

[22]  Ge-Xiang Zhang,et al.  Analyzing radar emitter signals with membrane algorithms , 2010, Math. Comput. Model..

[23]  Gheorghe Paun,et al.  The Oxford Handbook of Membrane Computing , 2010 .

[24]  Shu-Kai S. Fan,et al.  Optimal multi-thresholding using a hybrid optimization approach , 2005, Pattern Recognit. Lett..

[25]  Il Hong Suh,et al.  Dynamic multi-objective optimization based on membrane computing for control of time-varying unstable plants , 2011, Inf. Sci..

[26]  Amir Averbuch,et al.  Digital image thresholding, based on topological stable-state , 1996, Pattern Recognit..

[27]  Amitava Chatterjee,et al.  A hybrid cooperative-comprehensive learning based PSO algorithm for image segmentation using multilevel thresholding , 2008, Expert Syst. Appl..

[28]  Wenbing Tao,et al.  Image segmentation by three-level thresholding based on maximum fuzzy entropy and genetic algorithm , 2003, Pattern Recognit. Lett..

[29]  Hong Peng,et al.  Fuzzy reasoning spiking neural P system for fault diagnosis , 2013, Inf. Sci..