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改良遗传算法在图像多阈值分割中的应用 被引量:10

Improved Genetic Algorithm for Multi-Level Threshold Image Segmentation
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摘要 最大熵原则是图像阈值分割的一个重要方法。但是用此方法进行多阈值分割时,存在着计算开销巨大的问题。笔者在M.Srinivas的自适应遗传算法基础上提出一种改良的遗传算法,用于基于模糊最大熵图像多阈值分割,克服了此分割方法计算量大的问题。通过实验,比较了改良遗传算法和M.Srinivas自适应遗传算法及模拟退火算法,显示了改良遗传算法的有效性。 The maximum entropy approach is one of the most important threshold selection method. There exists a problem of computational prohibitive when fuzzy c partitions maximum entropy is applied to muli-level threshold selection. An improved genetic algorithm based on Srinivas Adaptive Genetic Algorithm is proposed to solve this problem. The results show that it can shorten the computation time compared with simulated annealing algorithm.
出处 《江苏大学学报(自然科学版)》 EI CAS 2003年第6期66-69,共4页 Journal of Jiangsu University:Natural Science Edition
基金 镇江市社会发展基金(SH2002039)
关键词 图像处理 阈值 模拟退火算法 遗传算法 image processing threshold simulated annealing algorithm genetic algorithm
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