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作 者:张铭凯 谷飞飞 肖振中 师少光 ZHANG Mingkai;GU Feifei;XIAO Zhenzhong;SHI Shaoguang(Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,China;Orbbec Inc.,Shenzhen 518057,China)
机构地区:[1]中国科学院深圳先进技术研究院,深圳518055 [2]奥比中光科技集团股份有限公司,深圳518057
出 处:《集成技术》2025年第1期50-64,共15页Journal of Integration Technology
基 金:国家自然科学基金项目(62105352);深圳市技术攻关重点项目(JSGG20220831092801003)。
摘 要:工业零部件边缘的精确重建是视觉定位和质量检测的前提和关键。针对工业零部件边缘处的点云难以精确重建的问题,该文提出一种基于点云投影的边缘三维重建算法。首先,通过双目结构光方法扫描得到零部件三维点云,提取扫描点云中的边缘点;其次,在双目图像中提取图像边缘点;再次,将点云边缘点投影到双目图像,在投影边缘点附近搜索最近邻的图像边缘点,匹配得到对应双目边缘点;最后,通过立体视觉方法重建精确的三维边缘点云。实验结果表明:与当前其他方法相比,该方法可有效解决反光、表面划痕等干扰导致的伪边缘问题,重建误差小于0.15 mm,可用于机器人上下料、在线质量检测等工业场景。The accurate reconstruction of industrial component edges is essential and crucial for visual positioning and quality inspection.To address the issue of difficulty in accurately reconstructing point clouds at the edges of industrial components,a three-dimensional edge reconstruction algorithm based on point cloud projection is proposed.First,the three-dimensional point cloud of the components is obtained by scanning using a binocular structured light method,edge points in the scanned point cloud are extracted.Then the image edge points are extracted from the binocular images.Subsequently,the point cloud edge points are projected onto the binocular images,the nearest image edge points are searched around each projected point to obtain corresponding binocular edge points.Finally,accurate three-dimensional edge point clouds are reconstructed using stereo vision methods.Experimental results demonstrate that compared to other current methods,this approach can effectively address the issue of false edges caused by interference such as reflection and surface scratches,the reconstructed edge point cloud using this method has high accuracy with reconstruction error less than 0.15 mm and can be applied in industrial scenarios such as bin picking,online quality inspection.
分 类 号:TP391.4[自动化与计算机技术—计算机应用技术]
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