A similarity metric for edge images

被引：64
|
作者：
Prieto, MS
Allen, AR
机构：
[1] Univ Aberdeen, Sch Engn & Phys Sci, Aberdeen AB24 3UE, Scotland
[2] Univ Aberdeen, Dept Biomed Phys & Bioengn, Aberdeen AB24 3UE, Scotland
来源：
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2003年 / 25卷 / 10期
关键词：
edge detection; image similarity; performance evaluation; pixel correspondence metric; weighted matching in bipartite graphs; matching problem; assignment problem;
D O I：
10.1109/TPAMI.2003.1233900
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The performance of several discrepancy measures for the comparison of edge images is analyzed and a novel similarity metric aimed at overcoming their problems is proposed. The algorithm finds an optimal matching of the pixels between the images and estimates the error produced by this matching. The resulting Pixel Correspondence Metric (PCM) can take into account edge strength as well as the displacement of edge pixel positions in the estimation of similarity. A series of experimental tests shows the new metric to be a robust and effective tool in the comparison of edge images when a small localization error of the detected edges is allowed.
引用
收藏
页码：1265 / 1273
页数：9
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