基于改进遗传算法的最大方差图像分割

Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007) Pub Date : 2007-07-30 DOI:10.1109/SNPD.2007.353

Wang Chun-mei, Wang Su-zhen, Zhang Chong-ming, Zou Jun-zhong

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引用次数: 4

摘要

提出了一种基于OTSU和改进遗传算法的图像分割方法。将OTSU作为评价函数，将分割问题转化为优化问题。即，遗传算法有效地搜索分割参数空间，以获得最优阈值。另一方面，为了克服遗传算法的局限性，采用了精英插入算法。实验结果表明，该方法不仅可以获得较好的结果，而且可以缩短处理时间。

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Maximum Variance Image Segmentation Based on Improved Genetic Algorithm

An image segmentation method based on the OTSU and improved genetic algorithm (GA) is presented. The OTSU is taken as evaluation function and the segmentation problem is turned to the optimization problem. That is, GA efficiently searches the segmentation parameter space in order to obtain the optimal threshold. On the other hand, to overcome some limitation of GA, elite reinsertion is applied. The experimental results indicate that the method can not only obtain a better result, but also shorten the processing time.

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来源期刊

Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)

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