吉林大学学报(理学版) ›› 2021, Vol. 59 ›› Issue (3): 568-576.

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基于Harris-改进LBP的特征匹配及目标定位算法

张震1, 张照崎2, 朱留存1, 苗志滨1, 王骥月1, 李修明3, 赵成龙1, 张坤伦1   

  1. 1. 北部湾大学 先端科学技术研究院, 广西 钦州 535001; 2. 大连理工大学-立命馆大学国际信息与软件学院, 辽宁 大连116085;
    3. 广西机械工业研究院有限责任公司, 广西 南宁 530007
  • 收稿日期:2020-07-13 出版日期:2021-05-26 发布日期:2021-05-23
  • 通讯作者: 朱留存 E-mail:lczhu@bbgu.edu.cn

Feature Matching and Target Location Algorithm Based on Harris Improved LBP

ZHANG Zhen1, ZHANG Zhaoqi2, ZHU Liucun1, MIAO Zhibin1,WANG Jiyue1, LI Xiuming3, ZHAO Chenglong1, ZHANG Kunlun1   

  1. 1. Research Institute of Advanced Science and Technology, Beibu Gulf University, Qinzhou 535001, Guangxi Zhuang Autonomous Region, China;
    2. DUT-RU International School of Information Science & Engineering at DUT, Dalian 116085, Liaoning Province, China;
    3. Guangxi Research Institute of Mechanical Industry Co. LTD, Nanning 530007, Guangxi Zhuang Autonomous Region, China
  • Received:2020-07-13 Online:2021-05-26 Published:2021-05-23

摘要: 为满足机器人伺服抓取中定位精度和实时性的要求, 提出一种基于Harris及改进局部二值模式(LBP)的特征匹配和目标定位快速算法. 首先采用Harris检测算法提取图像特征点; 然后提出一种新的特征点描述子定义方法, 先利用胡矩确定特征方向, 再根据特征方向对局部图像做标准化处理, 提取标准化局部图像LBP特征作为特征点描述子; 最后通过计算两张图像中各特征点描述子间的汉明距离实现特征匹配, 再根据匹配结果估计单应性矩阵, 定位目标在场景图像中的位置. 实验结果表明, 该算法匹配速度快、 定位精度高.

关键词: 特征检测, 特征匹配, 目标定位, 局部二值模式

Abstract: In order to meet the requirements of positioning accuracy and real-time in robot servo grasping, we proposed a fast algorithm of feature matching and target location based on Harris and improved local binary pattern (LBP). Firstly, Harris detection algorithm was adopted to extract the image feature points. Secondly, we proposed a new definition method of feature point descriptor. The Hu momen was used to determine the  feature directions, and then the local images were standardized according to the feature directions, and the LBP features of the standardized local image were extracted as the feature point descriptors. Finally, The features matching were realized by calculating the Hamming distance between the descriptors of each feature point in the two images, and then according to the matching results, the homography matrix was estimated to locate the position of target in the scene image. Experimental results show that the algorithm has fast matching speed and high positioning accuracy.

Key words: feature detection, feature matching, target location, local binary pattern

中图分类号: 

  • TP391.41