信息与控制2017，Vol.46Issue(3)：358-364,7.DOI:10.13976/j.cnki.xk.2017.0358
基于深度图像和点云边缘特征的典型零部件识别
Recognition of Typical Components Based on Edge Features of Depth Image and Point Cloud
摘要
Abstract
To solve the problem of component identification in automatic disassembly, a typical components identification method is proposed based on the depth image of Kinect and point cloud features.Firstly, a nonlinear filtering algorithm is used to process the acquired depth image and obtain the optimized point cloud target, and an eight neighborhood depth difference algorithm is proposed to extract the point cloud edge.The segmented point cloud edge is then detected using the RANSAC algorithm, and edge features are extracted to identify components.This method can identify typical components, and experimental results verify the effectiveness of the proposed method.关键词
Kinect传感器/点云数据/边缘提取/随机抽样一致性算法Key words
Kinect sensor/point cloud data/edge extraction/RANSAC algorithm分类
信息技术与安全科学引用本文复制引用
张志佳,魏信,周自强,吴天舒,贾梦思..基于深度图像和点云边缘特征的典型零部件识别[J].信息与控制,2017,46(3):358-364,7.基金项目
江苏省机电产品循环利用技术重点建设实验室基金资助项目(KF1508) （KF1508）
国家自然科学基金资助项目(61540069) （61540069）
