A modified Hausdorff distance using edge gradient for robust object matching

Zhi-qiang Zhou, Bo Wang
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引用次数: 13

Abstract

Conventional object matching algorithms based on Hausdorff distance mostly use edge position information to compute distances. In this paper we represent an edge point using its position and the strength of its gradient to define a 3D distance function. We propose a modified Hausdorff distance based on this 3D distance function, and investigate its application in object matching problems. Finally, experimental comparisons are performed with conventional methods. At this stage, we tested different methods on the images with different levels of noise. Their sensitivities to geometric distortion are also evaluated against image rotation and scale change. Experimental results show that the proposed algorithm is more robust and reliable.
基于边缘梯度的改进Hausdorff距离鲁棒目标匹配
传统的基于Hausdorff距离的目标匹配算法大多使用边缘位置信息来计算距离。在本文中,我们用边缘点的位置和梯度的强度来定义一个三维距离函数。在此基础上提出了一种改进的Hausdorff距离,并研究了其在目标匹配问题中的应用。最后,与常规方法进行了实验比较。在这个阶段,我们对不同噪声水平的图像进行了不同的方法测试。它们对几何畸变的敏感性也在图像旋转和尺度变化的情况下进行了评估。实验结果表明,该算法具有较好的鲁棒性和可靠性。
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