Robust and fast Hausdorff distance for image matching

Zhu, Hu; Zhang, Tianxu; Yan, Luxin; Deng, Lizhen

doi:doi:10.1117/1.OE.51.1.017203

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Optical Engineering / Volume 51 / Issue 1 / Machine Vision, Pattern Recognition

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Robust and fast Hausdorff distance for image matching

Opt. Eng. 51, 017203 (Jan 31, 2012); http://dx.doi.org/10.1117/1.OE.51.1.017203

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Abstract

References (13)

Citing Articles (15)

Hu Zhu, Tianxu Zhang, and Luxin Yan

Huazhong University of Science and Technology, State Key Laboratory for Multispectral Information Processing Technologies, Institute for Pattern Recognition and Artificial Intelligence, Wuhan 430074, China

Lizhen Deng

Huazhong University of Science and Technology, College of Electrical and Electronic Engineering, Wuhan 430074, China

A robust and fast Hausdorff distance (HD) method is presented for image matching. Canny edge operator is used for extracting edge points. HD measure is one of efficient measures for comparing two edge images by calculating the interpixel distance between two sets of edge points, and does not require the point-to-point correspondence. However, high computational complexity is a common problem for HD measure because a large number of edge points could be extracted used to calculate HD. Further, a great many incorrect edge points will be extracted under the condition of occlusion and other ill conditions. A gradient orientation selectivity strategy is proposed to not only select available edges, but also reduce the number of edge points. Experimental results show that the proposed method has less computational cost, and has good robustness for object matching, especially under partial occlusion and other ill conditions.

History

Received Aug 03, 2011
Revised Oct 08, 2011
Published online Jan 31, 2012

Digital Object Identifier

http://dx.doi.org/10.1117/1.OE.51.1.017203

Citation

Hu Zhu, Tianxu Zhang, Luxin Yan and Lizhen Deng, "Robust and fast Hausdorff distance for image matching", Opt. Eng. 51, 017203 (Jan 31, 2012); http://dx.doi.org/10.1117/1.OE.51.1.017203