Title :
Image segmentation based on fuzzy entropy and Bee Colony Algorithm
Author :
Yonghao Xiao ; Weiyu Yu ; Jing Tian
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
Image segmentation based on Bee Colony Algorithm (BCA) and fuzzy entropy is presented in this paper. The fuzzy entropy function is simplified with single parameter. The BCA is applied to search the minimum value of fuzzy entropy function. According to the minimum function value, the optimal image threshold is obtained. Experimental results are provided to demonstrate the superior performance of the proposed approach.
Keywords :
entropy; fuzzy set theory; image segmentation; optimisation; bee colony algorithm; fuzzy entropy function; image segmentation; minimum function value; optimal image threshold; Entropy; Equations; Image segmentation; Lead; Mathematical model; Noise; Optimization; Bee Colony Algorithm; Color image segmentation; Fuzzy Entropy; Image threshold;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583918
