摘要
为了解决平移、旋转、缩放和部分遮挡等复杂环境下的工件图像匹配识别问题,给出了一种基于SIFT(尺度不变特征变换)特征匹配的工件识别算法。该算法采用SIFT特征作为匹配特征,引入欧氏距离作为图像匹配的相似性度量,并采用设定阈值的方法剔除误配点。实验结果表明,该算法能有效解决具有平移、旋转、缩放和部分遮挡等情况下的工件匹配识别问题。
To solve the problem of work-piece image matching under the complex circumstance of translation, rotation, scale and part of occlusion, an algorithm of work-piece recognition based on SIFT （Scale Invariant Feature Transform） is suggested in this paper. The algorithm uses SIFT characteristics as matehing features, then introduces the Euclidean distance as the similarity metrics of image matching, and uses a method of setting a threshold value to delete the false matching points. The experimental results proved that the algorithm can effectively solve stereo matching problems of work-piece images including translation, rotation, scale and part of occlusion.
出处
《西安理工大学学报》
CAS
北大核心
2009年第2期202-206,共5页
Journal of Xi'an University of Technology
基金
国家自然科学基金资助项目(10872160)
陕西省教育厅省级重点实验室(机械制造装备重点实验室)重点科研计划项目(05JS29)
关键词
工件识别
特征提取
特征匹配
尺度不变特征变换
work-piece recognition
feature extraction
feature matching
scale invariant feature transform
