Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (8): 14-20.DOI: 10.3778/j.issn.1002-8331.1712-0376

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Research on Levy-DNA-ACO algorithm for medical image edge detection

ZHANG Jingyu, TENG Jianfu, BAI Yu   

  1. School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300072, China
  • Online:2018-04-15 Published:2018-05-02


张经宇,滕建辅,白  煜   

  1. 天津大学 电气自动化与信息工程学院,天津 300072

Abstract: Based on the new DNA-ant colony algorithm with Levy flight characteristics, this paper proposes a new intelligent optimization algorithm for medical image edge detection. The new DNA-ant colony algorithm with Levy flight characteristics can avoid the local optimum by utilizing the perturbation of Levy flight characteristics, and use the DNA crossover and mutation operation to regulate the parameters, so as to shorten the search time and improve the search accuracy. It uses the new improved ant colony algorithm to solve the medical image edge detection. And the results show that the improved ant colony algorithm is more precise and effective in solving this problem.

Key words: medical image, edge detection, ant colony optimization, Levy flight, DNA cross, DNA variation

摘要: 以带Levy飞行特性的新型DNA-蚁群算法为手段,提出了一种新的医学图像边缘检测优化智能算法。带Levy飞行特性的新型DNA-蚁群算法通过利用Levy飞行特性的扰动性避免基本算法陷入局部最优,利用DNA交叉与变异操作来调控算法参数,从而缩短搜索时间,提高搜索精度。利用新的改进蚁群算法解决医学图像边缘检测,实验仿真效果表明改进蚁群算法在解决医学图像边缘检测问题上更加精细,效果更好。

关键词: 医学图像, 边缘检测, 蚁群算法, Levy飞行, DNA交叉, DNA变异