一种快速准确的棋盘角点检测算法

Weixing Zhu, Changhua Ma, Libing Xia, Xin-cheng Li
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引用次数: 29

摘要

指出了SUSAN角点检测器在检测棋盘角点方面存在的局限性,在此基础上,基于USAN区域的对称几何结构,提出了一种改进的SUSAN角点检测器算法来检测棋盘角点。并将该算法应用于真实照片上的棋盘图像。改进后的算法可以从各个角度拍摄的真实照片中快速检测出角落。在亚像素级检测角点的理论是正交向量理论,即角点到其相邻区域像素点的向量应垂直于相邻区域像素点的灰度梯度。为了得到亚像素级的角点坐标,建立了邻域方程并采用迭代法求解,提出了根据透视投影中交叉比不变性来检验其有效性的方法。关键词:插入棋盘角;USAN;亚像素;交叉比不变性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fast and Accurate Algorithm for Chessboard Corner Detection
The authors point out the limitations of SUSAN corner detector in detecting chessboard corner, then describe an improved SUSAN(Smallest Univalue Segment Assimilating Nucleus) detector algorithm for detecting chessboard corner on the basis of symmetrical geometry structure of USAN (Univalue Segment Assimilating Nucleus) area. And the algorithm has been applied to the chessboard images on real photos. The improved algorithm can quickly detect corner from real photos shot from every angle. The theory of detecting corner at sub-pixel level is Orthogonal Vector Theory, that is, vector from the corner to its adjacent area pixel point should be vertical to gray grads of the adjacent area pixel point. In order to get the coordinate of corner at sub-pixel level, we establish the neighboring area equation and solve it via iterative method, and propose to check its validity according to cross ratio invariability in perspective projection. Keywords-insert chessboard corner; USAN; sub-pixel; cross ratio invariability
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