吉林大学学报(理学版) ›› 2021, Vol. 59 ›› Issue (5): 1171-1178.

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一种基于Shi-Tomasi和改进LBP的特征匹配及目标定位快速算法

张震1, 张照崎2, 朱留存1, 刘济尘3, 魏金占1, 蔡旭航1, 赵成龙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. 吉林大学 软件学院, 长春 130012
  • 收稿日期:2020-12-18 出版日期:2021-09-26 发布日期:2021-09-26
  • 通讯作者: 朱留存 E-mail:lczhu@bbgu.edu.cn

A Fast Algorithm for Feature Matching and Target Location Based on Shi-Tomasi and Improved LBP

ZHANG Zhen1, ZHANG Zhaoqi2, ZHU Liucun1, LIU Jichen3, WEI Jinzhan1, CAI Xuhang1, ZHAO Chenglong1   

  1. 1. Advanced Science and Technology Research Institute, 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. College of Software, Jilin University, Changchun 130012, China
  • Received:2020-12-18 Online:2021-09-26 Published:2021-09-26

摘要: 针对机器人伺服抓取中对定位精度和实时性均要求较高的问题, 提出一种特征匹配及目标定位快速算法. 首先, 采用Shi-Tomasi检测算法提取特征点; 其次, 提出一种新的特征描述子定义方法: 先以特征点为中心截取子图像, 利用二维Gauss函数偏导数确定特征方向, 再根据特征方向对局部图像做旋转处理, 提取旋转后标准局部图像局部二值模式作为特征描述子, 该描述子具有良好的局部性以及平移、 旋转不变性; 最后, 通过计算特征描述子间的Hamming距离实现特征匹配, 估计单应性矩阵, 定位目标在场景中的位置和方向. 实验结果表明, 该算法匹配速度快、 定位精度高、 稳定性好, 能满足机器人伺服抓取中定位精度和实时性的要求.

关键词: Shi-Tomasi检测算法, 特征检测, 特征匹配, 目标定位, 局部二值模式

Abstract: Aiming at the problem of high location precision and real-time in robot servo grasping, we proposed a fast algorithm for feature matching and target location. Firstly, Shi-Tomasi detection algorithm was adopted to extract the feature points. Secondly, a new definition method of feature descriptors was proposed, the sub-image was intercepted with the feature point as a center, and the feature direction was determined by the partial derivative of two-dimensional Gaussian function, the local image was rotated according to the feature direction, and the local binary pattern of the standard local image after rotation was extracted as the feature descriptor, which had good locality as well as invariance of translation and rotation. Finally, the feature matching was realized by calculating the Hamming distance between the feature descriptors, the homography matrix was estimated to locate the position and direction of the target in the scene. The experimental results show that the algorithm has the advantages of fast 
matching speed, high location precision and good stability, and can meet the requirements of location precision and real-time in robot servo grasping.

Key words: Shi-Tomasi detection algorithm, feature detection, feature matching, target location, local binary pattern (LBP)

中图分类号: 

  • TP391.41