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计算机工程 ›› 2012, Vol. 38 ›› Issue (21): 178-181. doi: 10.3969/j.issn.1000-3428.2012.21.048

• 人工智能及识别技术 • 上一篇    下一篇

基于细菌觅食优化算法的自适应阈值边缘检测

李 杰a,彭月英a,元昌安a,王仁民a,梁珺超b   

  1. (广西师范学院 a. 计算机与信息工程学院;b. 教育科学学院,南宁 530023)
  • 收稿日期:2011-12-19 出版日期:2012-11-05 发布日期:2012-11-02
  • 作者简介:李 杰(1986-),男,硕士研究生,主研方向:人工智能,数据挖掘;彭月英,教授;元昌安,教授、博士;王仁民、梁珺超,硕士研究生
  • 基金资助:
    广西自然科学基金资助重点项目(2011GXNSFD018025);广西教育厅科学研究与技术开发计划基金资助项目(桂科攻1114006-3B);广西研究生教育创新计划基金资助项目(2011106030703M05)

Adaptive Threshold Edge Detection Based on Bactrial Foraging Optimization Algorithm

LI Jie a, PENG Yue-ying a, YUAN Chang-an a, WANG Ren-min a, LIANG Jun-chao b   

  1. (a. School of Computer and Information Engineering; b. School of Education Science, Guangxi Teachers Education University, Nanning 530023, China)
  • Received:2011-12-19 Online:2012-11-05 Published:2012-11-02

摘要: Sobel算子在阈值偏高或偏低的情况下会产生伪边缘或边缘丢失的问题。为此,将细菌觅食优化算法与最大类间方差相结合,利用细菌觅食优化算法的全局寻优能力,以最大类间方差为适应度函数搜索最佳边缘检测阈值,对图像进行自动边缘检测。实验结果证明,该方法能够取得较好的边缘分割效果,提高阈值检索速度。

关键词: Sobel算子, 细菌觅食优化算法, 边缘检测, 遗传算法, 适应度函数

Abstract: Under the threshold high or low, Sobel operator will form the fake edge and the missing of edge. In order to overcome it, this paper proposes a new method which combines Bacterial Foraging Optimization(BFO) algorithm with Otsu algorithm, makes use of global optimization ability of BFO algorithm, uses the Otsu algorithm as the fitness function to search the best threshold, and automatically detects image edges. Experimental result shows that the method improves the retrieval speed of threshold and makes better effect of edge segmentation.

Key words: Sobel operator, Bacterial Foraging Optimization(BFO) algorithm, edge detection, Genetic Algorithm(GA), fitness function

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