摘要
针对仿射畸变问题,首先构建了基于最大稳定极值区域(MSER)的仿射不变性检测子:根据分离集合森林以及并查集算法提取极值区域,结合成分树和最大稳定判定条件提取MSER。以MSER为底层局部特征区域,生成SIFT描述子并聚类成视觉关键词表。利用标准加权思想,在检索图像上框选查询对象,根据库图像与查询对象的相似度对检索结果进行排序;同时,基于搜索单元区域匹配法的空间一致性度量准则,得到最终的检索结果。实验表明,该极值区域具有可靠的仿射不变性,所开发的检索机制也能显著提升图像检索系统的性能与可靠性。
This paper first introduces the Maximally Stable Extremal Region(MSER) detector,which is affine invariant.According to disjoint-set forests data structure and union-find,the extremal regions are extracted.And,combing the component tree and maximally stable extremal condition,the MSERs are obtained.Then the SIFT descriptors,which are used as local feature at low level,are produced in the MSER and then clustered into the visual 'words'.By using standard weighting,the query region is selected by the rectangle in the retrieval image.Based on the similarity of database images and the query regions,the image retrieval results are ranked.With spatial consistency measurement rule of regions matching method of search unit,the image retrieval results are obtained.The experiment shows these distinctive feature regions are invariant to the change in scale,rotation,translation and viewpoint,and the retrieval mechanism also improves the performance and reliability of image retrieve system greatly.Key words:image retrieval; affine invariance; maximally stable extremal regions; covariance matrix; visual
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2009年第7期959-963,共5页
Journal of Optoelectronics·Laser
基金
国家自然科学基金资助项目(60773056)
国家"863"计划资助项目(2007AA01Z416)
辽宁省自然科学基金资助项目(2051057)
