基于交叉熵和遗传算法的多级阈值分割方法

2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC) Pub Date : 2009-12-07 DOI:10.1109/ICICIC.2009.29

Shu-Chien Huang

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引用次数: 0

摘要

阈值选择是图像处理中的一个重要问题。本文提出了一种基于交叉熵的多级阈值分割的通用技术。然后，设计了一种专门用于搜索接近最优或最优阈值的遗传算法。利用已知图像验证了该方法的有效性和高效性。

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A Multilevel Thresholding Method Based on Cross Entropy and Genetic Algorithms

Threshold selection is one of the most important issues in image processing. In this paper, a general technique for multilevel thresholding based on cross entropy is proposed. Then, a genetic algorithm is designed especially for searching for the near-optimal or optimal thresholds. The effectiveness and efficiency of the proposed method is demonstrated by using well-known images.

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2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC)

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