基于混合遗传算法的数字图像相关方法

程振进; 王全保; 陈吉安; 赵海涛

doi:10.3788/OPE.20162413.0710

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基于混合遗传算法的数字图像相关方法

更新时间：2020-08-13

- 基于混合遗传算法的数字图像相关方法
- Digital image correlation method based on hybrid genetic algorithm
- 光学精密工程 2016年24卷第10s期页码：710-717
- 作者机构：
  
  上海交通大学航空航天学院上海,200240
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目（No.51205253）()
- DOI：10.3788/OPE.20162413.0710
  中图分类号： TP391.4
- 收稿日期：2016-05-19，
  
  修回日期：2016-06-05，
  
  纸质出版日期：2016-11-14
- 稿件说明：
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程振进, 王全保, 陈吉安等. 基于混合遗传算法的数字图像相关方法[J]. 光学精密工程, 2016,24(10s): 710-717

CHENG Zhen-jin, WANG Quan-bao, CHEN Ji-an etc. Digital image correlation method based on hybrid genetic algorithm[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 710-717
程振进, 王全保, 陈吉安等. 基于混合遗传算法的数字图像相关方法[J]. 光学精密工程, 2016,24(10s): 710-717 DOI： 10.3788/OPE.20162413.0710.

CHENG Zhen-jin, WANG Quan-bao, CHEN Ji-an etc. Digital image correlation method based on hybrid genetic algorithm[J]. Editorial Office of Optics and Precision Engineering, 2016,24(10s): 710-717 DOI： 10.3788/OPE.20162413.0710.

摘要

针对遗传算法应用于数字图像相关方法时呈现的局部搜索能力较弱、算法精度较低等特点，引入具有较强局部搜索能力的共轭梯度算子，以取长补短的原则进行混合遗传算法设计，以提高数字图像相关方法的精度及稳定性。首先，根据共轭梯度算子与遗传算法的不同结合方式，提出了3种有效的CG-GA混合算法：内嵌CG混合遗传算法，精英CG混合遗传算法以及并列CG混合遗传算法，并对这3种算法进行了原理性分析。然后，设计对比实验，基于预设位移的模拟散斑图，利用同参数的以上3种算法及标准RGA算法进行子区匹配搜索。最后，分析实验结果并对3种有效算法进行总结。以u方向为例，实验结果表明：内嵌CG混合遗传算法相比标准RGA算法减少了69.52%的平均误差，误差波动也有所减小，但计算消耗较大；精英CG混合遗传算法与并列CG混合遗传算法求解精度及稳定性大幅度提高，两者平均误差相比RGA减小了98.43%，具有较高的精度。在数字图像相关方法中，推荐使用后两种混合算法进行子区匹配搜索。

Abstract

In consideration of features presented of relatively weak local search ability

relatively low algorithm accuracy

etc with Genetic Algorithm(GA) applied to digital image correlation method

Conjugate Gradient(CG) method with strong local search capability was introduced; with the principle of complementarity

hybrid genetic algorithm was designed to improve the accuracy and stability of digital image correlation method. Firstly

according to different binding modes of CG and GA

three kinds of effective CG-GA hybrid algorithm were presented:embedded CG hybrid algorithm

elite CG hybrid genetic algorithm and parallel CG hybrid genetic algorithm. Then

principle analysis for these three algorithms was carried out. Next

based on simulated speckle pattern of preset displacement

contrast experiment between the above three algorithms with same parameter and standard RGA(Real-code Genetic Algorithm) for subarea matching search was designed. Lastly

Experimental results taking u direction as an example show that:mean error of embedded CG hybrid genetic algorithm is reduced by 69.52% compared with standard RGA algorithm with error fluctuation also reduced and relatively big calculation consumption; solution accuracy and stability of elite CG hybrid genetic algorithm and CG hybrid genetic algorithm are greatly improved; mean error between the two is reduced by 98.43% compared with RGA with high accuracy. In the digital image correlation method

the latter two hybrid algorithms are recommended for subarea matching search.

关键词

Keywords

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