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基于机器视觉的激光分区清洗轮廓识别方法 被引量:1

A Method of Contour Identification for Laser Partition Cleaning Based on Machine Vision
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摘要 针对工件表面局部破损漆层去除问题,实现激光分区高效清洗是提升清洗质量和效率的有效方法,而快速准确地识别局部破损漆层区域轮廓是分区清洗的前提。提出了基于机器视觉的激光分区清洗轮廓识别方法。针对相机曝光度较低,导致漆层区域轮廓难以识别问题,采用基于相机响应模型的图像增强方法;针对漆层区域复杂轮廓精准识别问题,提出基于色度坐标值的漆层轮廓识别方法;为实现激光分区高效清洗,采用基于最小外包络矩形的漆层区域复杂轮廓规则化方法,应用变间距清洗扫描路径。试验结果表明,该方法实现了低照度漆层区域复杂轮廓的精准识别,与传统迭代法相比,提高了轮廓识别准确性。 In view of the problem of removing local damaged paint layer on workpiece surface,it is an effective method to improve the cleaning quality and efficiency to implement the laser partition cleaning in high efficiency,and accurate identification of local damaged paint layer area contour is the premise of partition cleaning,therefore,a method of contour identification for laser partition cleaning based on machine vision is proposed.Aiming at the problem of difficulty to identify paint layer area contour caused by low camera exposure,an image enhancement method based on camera response model is adopted.Aiming at the problem of complex contour precise identification of paint layer area,a method of contour identification based on chroma coordinate value is proposed.In order to realize laser partition cleaning in high efficiency,a method of complex contour regularization of paint layer area based on minimum envelope rectangle is adopted,and a method of generation scanning path in variable distance is used.The experimental results show that this method achieves accurate identification of complex contour of paint layer area with low illumination,and improves the identification accuracy compared with the traditional iterative method.
作者 刘伟军 孙明阳 卞宏友 田泽琦 李强 王蔚 Liu Weijun;Sun Mingyang;Bian Hongyou;Tian Zeqi;Li Qiang;Wang Wei(School of Mechanical Engineering,Shenyang University of Technology,Shenyang,Liaoning 110870,China)
出处 《应用激光》 CSCD 北大核心 2022年第11期84-91,共8页 Applied Laser
基金 辽宁省揭榜挂帅科技攻关项目(2021JH1/10400077) 辽宁省“兴辽英才计划”项目(XLYC1902022) 辽宁省高校创新团队(20211402)。
关键词 激光清洗 图像增强 分区清洗 轮廓识别 laser cleaning image enhancement partition cleaning contour identification
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