基于Harris-改进LBP的特征匹配及目标定位算法

Feature Matching and Target Location AlgorithmBased on Harris Improved LBP

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.

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 defini tion method of feature point descriptor.The Hu momen was used to determine the feature directions,and then the local images were standardized according to t he 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.