CBIR(Content Based Im age Retrieval)是当前多媒体检索的热点 .颜色特征是图像检索的重要特征 .为了提高颜色特征的检索效果 ,在提取图像主色特征的基础上 ,进一步提取了相应的主色空间分布信息——主色矩特征 ,并建立了图像主色特征...CBIR(Content Based Im age Retrieval)是当前多媒体检索的热点 .颜色特征是图像检索的重要特征 .为了提高颜色特征的检索效果 ,在提取图像主色特征的基础上 ,进一步提取了相应的主色空间分布信息——主色矩特征 ,并建立了图像主色特征的描述模型 .在改进加权二次型相似性度量方法的基础上 ,提出主色多特征相似性度量方法 ,并对几种不同的相似性度量方案进行了对比 ,其中 DCME方法在 WWW发布方式的 CBIR原型系统上取得了较好的实验结果 .展开更多
Feature-based image matching algorithms play an indispensable role in automatic target recognition （ATR）. In this work, a fast image matching algorithm （FIMA） is proposed which utilizes the geometry feature of ext...Feature-based image matching algorithms play an indispensable role in automatic target recognition （ATR）. In this work, a fast image matching algorithm （FIMA） is proposed which utilizes the geometry feature of extended centroid （EC） to build affine invariants. Based on at-fine invariants of the length ratio of two parallel line segments, FIMA overcomes the invalidation problem of the state-of-the-art algorithms based on affine geometry features, and increases the feature diversity of different targets, thus reducing misjudgment rate during recognizing targets. However, it is found that FIMA suffers from the parallelogram contour problem and the coincidence invalidation. An advanced FIMA is designed to cope with these problems. Experiments prove that the proposed algorithms have better robustness for Gaussian noise, gray-scale change, contrast change, illumination and small three-dimensional rotation. Compared with the latest fast image matching algorithms based on geometry features, FIMA reaches the speedup of approximate 1.75 times. Thus, FIMA would be more suitable for actual ATR applications.展开更多
基金Projects(2012AA010901,2012AA01A301)supported by National High Technology Research and Development Program of ChinaProjects(61272142,61103082,61003075,61170261,61103193)supported by the National Natural Science Foundation of ChinaProjects(B120601,CX2012A002)supported by Fund Sponsor Project of Excellent Postgraduate Student of NUDT,China
文摘Feature-based image matching algorithms play an indispensable role in automatic target recognition （ATR）. In this work, a fast image matching algorithm （FIMA） is proposed which utilizes the geometry feature of extended centroid （EC） to build affine invariants. Based on at-fine invariants of the length ratio of two parallel line segments, FIMA overcomes the invalidation problem of the state-of-the-art algorithms based on affine geometry features, and increases the feature diversity of different targets, thus reducing misjudgment rate during recognizing targets. However, it is found that FIMA suffers from the parallelogram contour problem and the coincidence invalidation. An advanced FIMA is designed to cope with these problems. Experiments prove that the proposed algorithms have better robustness for Gaussian noise, gray-scale change, contrast change, illumination and small three-dimensional rotation. Compared with the latest fast image matching algorithms based on geometry features, FIMA reaches the speedup of approximate 1.75 times. Thus, FIMA would be more suitable for actual ATR applications.
