激光技术Issue(3)：364-367,4.DOI:10.7510/jgjs.issn.1001-3806.2014.03.017
基于新遗传算法的 Otsu图像阈值分割方法
Otsu image threshold segmentation method based on new genetic algorithm
王宏文 1梁彦彦 1王志华1
作者信息
- 1. 河北工业大学控制科学与工程学院，天津300130
- 折叠
摘要
Abstract
Maximum between-class variance ( Otsu ) image segmentation method is a common image threshold segmentation method based on statistical theory , but Otsu image segmentation method has some disadvantages , such as more time-consuming , low segmentation accuracy and false image segmentation .Combining the principles of monkey king genetic algorithms, with Otsu algorithm, image gray, just as optimal threshold, was found.The results show that combined method not only improves the quality of image segmentation but also reduce the computation time .It is very suitable for real-time image processing .关键词
图像处理/最佳阈值/猴王遗传算法/最大类间方差Key words
image processing/optimal threshold/monkey king genetic algorithm/maximum between-class variance分类
信息技术与安全科学引用本文复制引用
王宏文,梁彦彦,王志华..基于新遗传算法的 Otsu图像阈值分割方法[J].激光技术,2014,(3):364-367,4.
