计算机技术与发展2016，Vol.26Issue(7)：30-35,6.DOI:10.3969/j.issn.1673-629X.2016.07.007
基于离散灰狼算法的多级阈值图像分割
A Multi-threshold Image Segmentation Algorithm Based on Discrete Grey Wolf Optimization
摘要
Abstract
The key of threshold segmentation is to select the thresholds which can determine the result of segmentation. With the increas-ing amounts of thresholds,the computation complexity gets higher. In this paper,a Discrete Grey Wolf Optimization ( DGWO) is pro-posed to select the appropriate thresholds for image segmentation and apply it to the global optimization problem of objective function of Kapur segmentation function. The DGWO can be well blended into image segmentation. It specially suits for solving complex function with high-dimension and multi-peak for its excellent performance in global convergence,robustness and ability to avoid trapping into lo-cal optimization. Extensive theoretical analysis and the results of simulation have shown that DGWO has better effectiveness,efficiency, stability of the range of thresholds and quality in multi-images and multi-thresholds segmentation compared with GA and PSO.关键词
图像分割/优化算法/离散灰狼算法/Kapur熵Key words
image segmentation/optimization algorithm/Discrete Grey Wolf algorithm ( DGWO)/Kapur entropy分类
信息技术与安全科学引用本文复制引用
王钛,许斌,李林国,亓晋..基于离散灰狼算法的多级阈值图像分割[J].计算机技术与发展,2016,26(7):30-35,6.基金项目
国家自然科学基金资助项目(61401225) （61401225）
南京邮电大学引进人才科研启动基金(NY213047,NY214102,NY213050,NY214098) （NY213047,NY214102,NY213050,NY214098）
