The Application of a New Entropy Function and Mutative Scale Chaos Optimization Strategy in Two-Dimensional Entropic Image Segmentation

A novel two dimensional entropic image segmentation method is presented in this paper The method makes use of a new entropy function defined in a simple form, which can reduce computational amount notably. And the correctness of the new function is also proved. Then a strategy of mutative scale chaos optimization is adopted to search for the optimal threshold. The results of simulation illustrate that efficiency of segmentation is improved significantly due to the new entropy function and search method

[1]  Song Jin-gui.  Image Segmentation Based on Optimal Histogram Threshold by Improved Genetic Algorithms , 2005 .

[2]  S. Pal,et al.  Object-background segmentation using new definitions of entropy , 1989 .

[3]  Gao Liqun.  Improvement of 2-D Maximum Entropy Threshold Algorithm Based on Optimal Entropy Function , 2005 .

[4]  Keiichiro Yasuda,et al.  Global optimization method using chaos in dissipative system , 1996, Proceedings of the 1996 IEEE IECON. 22nd International Conference on Industrial Electronics, Control, and Instrumentation.

[5]  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..

[6]  Ahmed S. Abutableb.  Automatic thresholding of gray-level pictures using two-dimensional entropy , 1989 .

[7]  Darrel L. Chenoweth,et al.  Two-dimensional entropic segmentation , 1999, Pattern Recognit. Lett..

[8]  Kazuyuki Aihara,et al.  Adaptive annealing for chaotic optimization , 1996 .

[9]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[10]  Kazuyuki Aihara,et al.  Global searching ability of chaotic neural networks , 1999 .

[11]  C. H. Lie,et al.  Segmentation of die patterns using minimum cross entropy , 1992, Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation.

[12]  Xin Wang,et al.  X-ray image segmentation based on genetic algorithm and maximum fuzzy entropy , 2004, IEEE Conference on Robotics, Automation and Mechatronics, 2004..