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• W2066624036 abstract "Image matching has been a central problem in computer vision and image processing for decades. Most of the previous approaches to image matching can be categorized into the intensity-based and edge-based comparison. Hausdorff distance has been widely used for comparing point sets or edge maps since it does not require point correspondences. In this paper, we propose a new image similarity measure combining the Hausdorff distance with a normalized gradient consistency score for image matching. The normalized gradient consistency score is designed to compare the normalized image gradient fields between two images to alleviate the illumination variation problem in image matching. By combining the edge-based and intensity-based information for image matching, we are able to achieve robust image matching under different lighting conditions. We show the superior robustness property of the proposed image matching technique through experiments on face recognition under different lighting conditions." @default.
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• W2066624036 date "2007-04-01" @default.
• W2066624036 modified "2023-10-16" @default.
• W2066624036 title "Hybrid image matching combining Hausdorff distance with normalized gradient matching" @default.
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• W2066624036 doi "https://doi.org/10.1016/j.patcog.2006.09.014" @default.
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