Cross-Weighted Centroid with Application to the Extraction of Affine Invariants

Xiangjun Zhao, Jianwei Yang, Rushi Lan, Wensheng Chen
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Abstract

In this paper, cross-weighted centroid (CWC) is constructed to extract affine invariant features. Every point in an image is assigned with a cross-weight based on the distribution of the image. CWC, derived from these weighted points, is affine invariance. Based on the original centroid and CWC of the image, a series of centroids of some affine regions can be obtained by iterating affine region cutting, i.e., ARC. Several affine invariant triangles are constructed. Consequently, affine invariant features can be derived by the area of these triangles. Experiment results show the efficiency of the proposed method.
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交叉加权质心在仿射不变量提取中的应用
本文构造了交叉加权质心(CWC)来提取仿射不变特征。根据图像的分布给图像中的每个点分配一个交叉权值。由这些加权点导出的CWC是仿射不变性。在图像原始质心和CWC的基础上,通过迭代仿射区域切割得到一系列仿射区域的质心,即ARC。构造了几个仿射不变三角形。因此,仿射不变特征可以由这些三角形的面积导出。实验结果表明了该方法的有效性。
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