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A novel starting-point-independent wavelet coefficient shape matching (EI CONFERENCE)

文献类型：会议论文

作者Hu S. ; Zhu M. ; Wu C. ; Song H.-J.
出版日期2006
会议名称ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005
会议地点Changchun, China
关键词In many computer vision tasks in order to improve the accuracy and robustness to the noise wavelet analysis is preferred for the natural multi-resolution property. However the wavelet representation suffers from the dependency of the starting point of the sampled contour. For overcoming the problem that the wavelet representation depends on the starting point of the sampled contour the Zernike moments are introduced and a novel Starting-Point-lndependent wavelet coefficient shape matching algorithm is presented. The proposed matching algorithm firstly gains the object contours and give the translation and scale invariant object shape representation. The object shape representation is converted to the dyadic wavelet representation by the wavelet transform. And then calculate the Zernike moments of wavelet representation in different scales. With respect to property of rotation invariant of Zernike moments consider the Zernike moments as the feature vector to calculate the dissimilarity between the object and template image which overcoming the problem of dependency of starting point. The experimental results have proved the proposed algorithm to be efficient precise and robust.
收录类别EI
源URL[http://ir.ciomp.ac.cn/handle/181722/33654]  
专题长春光学精密机械与物理研究所_中科院长春光机所知识产出_会议论文
推荐引用方式
GB/T 7714		 Hu S.,Zhu M.,Wu C.,et al. A novel starting-point-independent wavelet coefficient shape matching (EI CONFERENCE)[C]. 见:ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005. Changchun, China.

入库方式： OAI收割

来源：长春光学精密机械与物理研究所

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