[1]贲晛烨,孙孟磊,张鹏,等.基于Gabor-BLPOC的指关节纹识别算法[J].东南大学学报(自然科学版),2014,44(6):1121-1125.[doi:10.3969/j.issn.1001-0505.2014.06.005]
 Ben Xianye,Sun Menglei,Zhang Peng,et al.Finger-knuckle-print recognition based on Gabor-BLPOC[J].Journal of Southeast University (Natural Science Edition),2014,44(6):1121-1125.[doi:10.3969/j.issn.1001-0505.2014.06.005]
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基于Gabor-BLPOC的指关节纹识别算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
44
期数:
2014年第6期
页码:
1121-1125
栏目:
计算机科学与工程
出版日期:
2014-11-20

文章信息/Info

Title:
Finger-knuckle-print recognition based on Gabor-BLPOC
作者:
贲晛烨12孙孟磊1张鹏12王卓然1孟维晓3
1山东大学信息科学与工程学院, 济南250100; 2南京理工大学高维信息智能感知与系统教育部重点实验室, 南京210094; 3哈尔滨工业大学电子与信息工程学院, 哈尔滨150080
Author(s):
Ben Xianye12 Sun Menglei1 Zhang Peng12 Wang Zhuoran1 Meng Weixiao3
1School of Information Science and Engineering, Shandong University, Jinan 250100, China
2Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, Nanjing University of Science and Technology, Nanjing 210094, China
3School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150080, China
关键词:
指关节纹识别 Gabor滤波器 带限相位相关 互功率谱
Keywords:
finger-knuckle-print(FKP)recognition Gabor filter band-limited phase-only correlation(BLPOC) cross power spectrum
分类号:
TP391.41
DOI:
10.3969/j.issn.1001-0505.2014.06.005
摘要:
指关节纹比手掌特征更明显,针对这种生物特征提出一种基于Gabor-带限相位相关(Gabor-BLPOC)的指关节纹识别算法.首先,使用Gabor滤波器抑制噪声,并采用限制对比度自适应直方图均衡化对指关节纹图像进行增强;其次,使用BLPOC算法提取指关节纹图像的相位特征;然后,通过计算2幅指关节纹图像的互功率谱对指关节纹图像进行校准;最后,再次计算校准后图像的BLPOC,根据2幅图像的互功率谱峰值进行指关节纹图像的匹配.通过在PolyU FKP数据库上的实验表明,所提出算法的等错误率为1.57%,具有更加精确的匹配效果,从而验证了该算法的有效性.
Abstract:
Since finger-knuckle-print(FKP)is endowed with more recognizable features than palm character, a novel finger-knuckle-print recognition algorithm based on Gabor and band-limited phase-only correlation(Gabor-BLPOC)is proposed. First, Gabor filter is used to reduce noise, and contrast-limited adaptive histogram equalization is employed to enhance the FKP image. Secondly, BLPOC is used to extract the phase feature of the FKP image. Then, the cross power spectrum of two FKP images is computed to calibrate the images. Finally, BLPOC of the calibrated images is calculated again, and FKP image matching is achieved according to the peak value of the cross power spectrum. Experiments on the PolyU FKP database are carried out, and it is shown that the proposed algorithm can achieve an equal error rate(EER)of 1.57%, which verifies the effectiveness of the proposed scheme.

参考文献/References:

[1] Kumar A, Zhou Y. Human identification using knucklecodes [C]//IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems. Washington, DC, 2009: 1-6.
[2] Kumar A, Ravikanth C. Personal authentication using finger knuckle surface [J]. IEEE Transactions on Information Forensics and Security, 2009, 4(1): 98-110.
[3] Xiong M, Yang W K, Sun C Y. Finger-knuckle-print recognition using LGBP [M]//Advances in Neural Networks. Berlin: Springer, 2011: 270-277.
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[6] Zhang L, Zhang L, Zhang D. Finger-knuckle-print verification based on band-limited phase-only correlation[C]//Computer Analysis of Images and Patterns. Münster, Germany, 2009: 141-148.
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备注/Memo

备注/Memo:
收稿日期: 2014-07-25.
作者简介: 贲晛烨(1983—),女,博士,讲师,benxianyeye@163.com.
基金项目: 国家自然科学基金资助项目(61201370)、教育部博士点基金资助项目(20120131120030)、中国博士后科学基金资助项目(2013M530321)、中国博士后科学基金特别资助项目(2014T70636)、山东省博士后创新项目专项资金资助项目(201303100)、山东大学自主创新基金资助项目(2012GN043)、高维信息智能感知与系统教育部重点实验室(南京理工大学)基金资助项目(30920140122006).
引用本文: 贲晛烨,孙孟磊,张鹏,等.基于Gabor-BLPOC的指关节纹识别算法[J].东南大学学报:自然科学版,2014,44(6):1121-1125. [doi:10.3969/j.issn.1001-0505.2014.06.005]
更新日期/Last Update: 2014-11-20