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基于遗传算法的激光视觉焊缝特征点提取

Feature Points Extraction of Laser Vision Weld Seam Based on Genetic Algorithm

张斌   常森   王桔   王倩  
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摘要

提出了一种基于遗传算法的平面焊缝特征点提取方法。采用中值滤波、阈值分割法对焊缝图像进行预处理, 以减少噪声; 利用种子填充法进行图像分割, 提取出激光条纹连通域, 根据连通域特征抽象出激光条纹骨架提取的数学模型; 重点研究基于遗传算法的骨架提取方法, 并采用法向直线扫描法沿骨架方向提取中心点坐标; 对骨架中心点进行直线拟合, 并利用拉依达准则迭代剔除噪声点, 获得激光条纹骨架的准确位置和焊缝特征点坐标。经试验验证可知, 该方法能够有效消除焊缝图像中多种噪声及激光条纹宽度的干扰, 快速准确地检测出焊缝特征点的位置。

Abstract

A method for feature points extraction of planar weld seams based on genetic algorithm is proposed. In order to reduce the image noises, we use median filtering method and threshold segmentation method to preprocess welding images. The seed filling method is used for the image segmentation, and the mathematical model of laser stripe skeleton extraction is obtained according to the characteristics of the image. The skeleton extraction method of laser stripe based on genetic algorithm is mainly studied, and the coordinate of center point is extracted with linear scanning method. The Pauta criterion is used during the linear fitting of the skeleton to iteratively eliminate the noise data, and the accurate position of the skeleton and feature points are obtained. The experimental results show that the method can effectively eliminate many noises and the interference of laser stripe width in weld image and can extract the weld feature points quickly and accurately.

Newport宣传-MKS新实验室计划
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中图分类号:TP391

DOI:10.3788/cjl201946.0102001

所属栏目:激光制造

基金项目:浙江省自然科学基金(LY17E050015)

收稿日期:2018-07-09

修改稿日期:2018-08-03

网络出版日期:2018-08-24

作者单位    点击查看

张斌:中国计量大学计量测试工程学院, 浙江 杭州 310018
常森:中国计量大学计量测试工程学院, 浙江 杭州 310018
王桔:中国计量大学计量测试工程学院, 浙江 杭州 310018
王倩:中国计量大学计量测试工程学院, 浙江 杭州 310018

联系人作者:张斌(zhwwbin@cjlu.edu.cn)

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引用该论文

Zhang Bin,Chang Sen,Wang Ju,Wang Qian. Feature Points Extraction of Laser Vision Weld Seam Based on Genetic Algorithm[J]. Chinese Journal of Lasers, 2019, 46(1): 0102001

张斌,常森,王桔,王倩. 基于遗传算法的激光视觉焊缝特征点提取[J]. 中国激光, 2019, 46(1): 0102001

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