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作 者:刘群坡[1] 席秀蕾 杨凌霄[1] LIU Qunpo;XI Xiulei;YANG Lingxiao(School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo 454000,China)
机构地区:[1]河南理工大学电气工程与自动化学院,河南焦作454000
出 处:《电子科技》2022年第5期1-6,13,共7页Electronic Science and Technology
基 金:国家重点研发计划(2016YFC0600906);河南省高校科技创新团队(20IRTSTHN019);河南省创新型科技人才队伍建设工程(CXTD2016054);河南理工大学博士基金(722103/001/070)。
摘 要:针对AKAZE算法在玻璃封装电连接器图像匹配中准确率低及耗时长的问题,文中提出了基于LK光流和网格运动统计的图像匹配改进算法。首先采用AKAZE算法提取玻璃封装电连接器特征点,运用M-LDB描述子进行特征描述。然后利用LK光流法计算匹配区域进行条件约束,从而得到匹配点,并通过FLANN算法进行特征匹配。最后将玻璃封装电连接器图像划分为多个网格,计算FLANN匹配好的特征点邻域的正确匹配个数和阈值并剔除误匹配点。文中实验采用公开数据集和玻璃封装电连接器数据,从实时性和准确性两方面对算法性能进行验证分析。结果表明,改进的算法在处理模糊、亮度及旋转变化的玻璃封装电连接器图像对时,其匹配准确率均达到93%以上,耗时为0.4 s内,证明了算法的有效性。In order to solve the low accuracy and time-consuming problem of AKAZE algorithm in the image matching of glass-encapsulated electrical connectors,improved image matching algorithm based on LK optical flow and grid motion statistics is proposed in this study.First,the AKAZE algorithm is used to extract feature points,and the M-LDB descriptor is used to describe the features.Then,LK optical flow method is used to calculate the matching area for conditional constraints to obtain matching points,and the FLANN algorithm is adopted for feature matching.Finally,the glass-encapsulated electrical connector image is divided into multiple grids,and the numbers and threshold values of correct matching points of the neighborhood of the feature points that are matched by FLANN are calculated to eliminate the wrong matching points.By using public datasets and glass-encapsulated electrical connector data,the performance of the algorithm is verified and analyzed from both real-time and accuracy aspects.The results show that the improved algorithm has a matching accuracy of more than 93%when dealing with image pairs of glass-encapsulated electrical connectors with blur,brightenss and rotation changes,and the time-consuming is within 0.4 s,which proves the effectiveness of the algorithm.
关 键 词:双目视觉定位 玻璃封装电连接器 AKAZE算法 LK光流 特征 匹配 FLANN算法 网格运动统计
分 类 号:TP391[自动化与计算机技术—计算机应用技术] TN99[自动化与计算机技术—计算机科学与技术]
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