A systematic method for fingerprint ridge orientation estimation and image segmentation

被引:85
作者
Zhu, En [1 ]
Yin, Jianping [1 ]
Hu, Chunfeng [1 ]
Zhang, Guomin [1 ]
机构
[1] Natl Univ Def Technol, Sch Comp Sci, Changsha 410073, Peoples R China
基金
中国国家自然科学基金;
关键词
ridge orientation; neural network; fingerprint segmentation; remaining ridges; secondary segmentation; segmentation revision; minutiae detection;
D O I
10.1016/j.patcog.2006.03.001
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a scheme for systematically estimating fingerprint ridge orientation and segmenting fingerprint image by means of evaluating the correctness of the ridge orientation based on neural network. The neural network is used to learn the correctness of the estimated orientation by gradient-based method. The trained network is able to distinguish correct and incorrect ridge orientations, and as a consequence, the falsely estimated ridge orientation of a local image block can be corrected using the around blocks of which orientations are correctly estimated. A coarse segmentation can also be done based on the trained neural network by taking the blocks of correctly estimated orientation as foreground and the blocks of incorrectly estimated orientation as background. Besides, following the steps of estimating ridge orientation correctness, a secondary segmentation method is proposed to segment the remaining ridges which are the afterimage of the previously scanned fingers. The proposed scheme serves for minutiae detection and is compared with VeriFinger 4.2 published by Neurotechnologija Ltd. in 2004, and the comparison shows that the proposed scheme leads to an improved accuracy of minutiae detection. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1452 / 1472
页数:21
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