用于指纹图像质量评价的新特征集

doi:10.13229/j.cnki.jdxbgxb201403042

吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (3): 840-846.doi: 10.13229/j.cnki.jdxbgxb201403042

用于指纹图像质量评价的新特征集

袁宝玺^1,2,3,苏菲^1,3,赵志诚^1,3,蔡安妮^1,3

1.北京邮电大学信息与通信工程学院,北京 100876;
2.中国人民解放军95949部队,河北沧州 061736;
3.北京邮电大学网络系统与网络文化北京市重点实验室,北京 100876

收稿日期:2012-12-05 出版日期:2014-03-01 发布日期:2014-03-01
通讯作者: 苏菲(1973),女,教授,博士生导师.研究方向:多媒体技术与信息处理.E-mail:sufei@bupt.edu.cn E-mail:13811255231@qq.com
作者简介:袁宝玺(1978),男,工程师,博士.研究方向:多媒体技术与信息处理.E-mail:13811255231@qq.com
基金资助:
国家自然科学基金项目(90920001, 61101212);“863”国家高技术研究发展计划项目(2012AA012505);教育部归国留学人员科研启动基金项目.

Novel feature set for fingerprint image quality assessment

YUAN Bao-xi^1,2,3,SU Fei^1,3,ZHAO Zhi-Cheng^1,3,CAI An-ni^1,3

1.School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2.The Chinese People′s Liberation Army 95949 Troops, Cangzhou 061736 China;
3.Beijing Key Laboratory of Network System and Network Culture, Beijing University of Posts and Telecommunications, Beijing 100876,China

Received:2012-12-05 Online:2014-03-01 Published:2014-03-01

摘要/Abstract

摘要： 以视觉注意机理为依据来选取指纹图像质量评价的特征,使特征集能够全面覆盖人对图像进行评价的各个方面。同时,提出了基于极坐标中心敏感特性的细节点可靠性评价方法和基于Otsu算法的灰度对比度评价方法。根据这些方法提取的特征能够更准确地描述图像的质量状态。试验结果表明:本文的特征集在BP神经网络和SVM两种分类器上都获得了很高的分类准确率。

关键词: 信息处理技术, 指纹质量评价, 视觉注意机制, 细节点可靠性评价, 灰度对比度评价

Abstract: Based on the mechanism of human visual attention, five features are chosen to simulate the process of subjective quality assessment of fingerprint images. Among these features, two of them are extracted by two proposed methods, a minutiae reliability assessment based on Polar Coordinates Centrum Sensitivity (PCCS) and a gray-scale image contrast based on Otsu algorithm. Experimental results show that this feature set on both Error Back Propagation (BP) Neural Network and Support Vector Machine (SVM) gives high classification accuracy.

Key words: information processing technology, fingerprint image quality assessment, mechanism of visual attention, minutiae reliability assessment, gray scale image contrast assessment

中图分类号:

TN911.73

袁宝玺,苏菲,赵志诚,蔡安妮. 用于指纹图像质量评价的新特征集[J]. 吉林大学学报(工学版), 2014, 44(3): 840-846.

YUAN Bao-xi,SU Fei,ZHAO Zhi-Cheng,CAI An-ni. Novel feature set for fingerprint image quality assessment[J]. 吉林大学学报(工学版), 2014, 44(3): 840-846.

参考文献

[1] Yang Zhi-guo, Li Ya-shuo, Yin Yi-long, et al. A template selection method based on quality for fingerprint matching[C]∥9th International Conference on Fuzzy Systems and Knowledge Discovery, Sichuan, 2012: 1382-1385.
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用于指纹图像质量评价的新特征集

Novel feature set for fingerprint image quality assessment

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