电子科技2024，Vol.37Issue(4)：55-61,7.DOI:10.16180/j.cnki.issn1007-7820.2024.04.008
基于改进ORB-FLANN算法的工件图像识别方法
Workpiece Image Recognition Method Based on Improved ORB-FLANN Algorithm
摘要
Abstract
In view of the problems of low matching rate and long running time of traditional image recognition algorithms,an improved ORB-FLANN(Oriented FAST and Rotated BRIEF-Fast Library for Approximate Nearest Neighbors)based workpiece image recognition method is proposed.The feature description of ORB algorithm and im-age feature matching algorithm are modified to solve the disadvantages of traditional image recognition algorithm in the case of scale and rotation transformation and reduce the mismatching rate of matching.For the feature points detected by ORB algorithm,SURF(Speeded Up Robust Features)algorithm is used to add orientation information and com-plete the feature description,so as to obtain the feature points with rotation-scale invariance.FLANN algorithm is combined with bidirectional matching strategy for coarse matching of feature points.Finally,the progressive sampling-congruence algorithm is used to further eliminate the mismatched point pairs and complete the fine matc-hing.The experimental results show that compared with other methods,the improved algorithm can improve the matc-hing accuracy of 2.6%～18.8%and 29.5%～43.9%,respectively,when processing scale and rotation transform images,and the running time is within 4s,improving the efficiency and accuracy of workpiece image recognition.关键词
图像识别/ORB算法/SURF算法/FLANN算法/双向匹配/渐进采样一致/匹配正确率/工件图像Key words
image recognition/ORB algorithm/SURF algorithm/FLANN algorithm/bidirectional matching/PRO-SAC/rate of matching/workpiece image分类
信息技术与安全科学引用本文复制引用
朱志浩,鹿志旭,郭毓,高直..基于改进ORB-FLANN算法的工件图像识别方法[J].电子科技,2024,37(4):55-61,7.基金项目
国家自然科学基金(61973167) （61973167）
盐城工学院校级科研项目(XJR2020041)National Natural Science Foundation of China(61973167) （XJR2020041）
Universi-ty-Level Scientific Research Project of Yancheng Institute of Tech-nology(XJR2020041) （XJR2020041）
