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A Linear Time Algorithm of Computing Hausdorff Distance for Content-based Image Analysis

机译:基于Hausdorff距离的线性时间算法用于基于内容的图像分析

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摘要

The Hausdorff distance is a very important metric for various image applications in computer vision including image matching, moving-object detection, tracking and recognition, shape retrieval and content-based image analysis. However, no efficient algorithm has been reported that computes the exact Hausdorff distance in linear time for comparing two images. Very few methods have been proposed to compute the approximate Hausdorff distance with higher approximation error. In this paper, we propose a linear time algorithm for computing the approximated Hausdorff distance with lower approximation error. The proposed method is effective to reduce the processing time, while minimizing the error rate in content-based image processing and analysis.
机译:Hausdorff距离是计算机视觉中各种图像应用程序(包括图像匹配,运动对象检测,跟踪和识别,形状检索以及基于内容的图像分析)的非常重要的指标。但是,还没有有效的算法可以计算出线性时间中精确的Hausdorff距离,以比较两个图像。很少有人提出具有较高近似误差的近似Hausdorff距离的计算方法。在本文中,我们提出了一种线性时间算法,用于以较低的近似误差计算近似的Hausdorff距离。所提出的方法有效地减少了处理时间,同时最小化了基于内容的图像处理和分析中的错误率。

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