Fake Fingerprint Detection Based on Wavelet Analysis and Local Binary Pattern

被引：0

作者：

Zhang, Yongliang ^{[1
]}

Fang, Shanshan ^{[1
]}

Xie, Yu ^{[2
]}

Xu, Tingting ^{[3
]}

机构：

[1] Zhejiang Univ Technol, Coll Comp Sci & Technol, Hangzhou, Zhejiang, Peoples R China

[2] Hangzhou Jinglianwen Technol Co Ltd, Hangzhou, Zhejiang, Peoples R China

[3] Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou, Zhejiang, Peoples R China

来源：

BIOMETRIC RECOGNITION (CCBR 2014) | 2014年 / 8833卷

关键词：

wavelet analysis; LBP; SVM; fake fingerprint detection; CLASSIFICATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Fake fingerprint detection technology is used for detecting spoof fingerprint attacks in biometric systems. In this paper, an improved software-based fake fingerprint detection approach using wavelet analysis and local binary pattern(LBP) is proposed. Firstly, wavelet analysis is applied to get the denoised image and residual noise image. Then both two images are divided into blocks of the same size to calculate the histogram of LBP as features, which provide more texture information than the features in original wavelet-based method. Finally, support vector machine(SVM) is used for classification. The average rate of accuracy of the proposed approach is 88.53% for all datasets in LivDet2011, and 88.98% in LiveDet2013, while the winner in LivDet2011 is 74.41%, and the winner in LivDet2013 is 86.63%.

引用

页码：191 / 198

页数：8

共 11 条

[1]

Ahonen T, 2004, LECT NOTES COMPUT SC, V3021, P469

[2] Fake finger detection by skin distortion analysis [J].

Antonelli, Athos ;

Cappelli, Raffaele ;

Maio, Dario ;

Maltoni, Davide .

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2006, 1 (03) :360-373

[3] Risk evaluation for spoofing against a sensor supplied with liveness detection [J].

Espinoza, Marcela ;

Champod, Christophe .

FORENSIC SCIENCE INTERNATIONAL, 2011, 204 (1-3) :162-168

[4] A high performance fingerprint liveness detection method based on quality related features [J].

Galbally, Javier ;

Alonso-Fernandez, Fernando ;

Fierrez, Julian ;

Ortega-Garcia, Javier .

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2012, 28 (01) :311-321

[5]

Ghiani L, 2013, INT CONF BIOMETR, DOI 10.1109/ICB.2013.6613027

[6] Wavelet based fingerprint liveness detection [J].

Moon, YS ;

Chen, JS ;

Chan, KC ;

So, K ;

Woo, KC .

ELECTRONICS LETTERS, 2005, 41 (20) :1112-1113

[7] A comparative study of texture measures with classification based on feature distributions [J].

Ojala, T ;

Pietikainen, M ;

Harwood, D .

PATTERN RECOGNITION, 1996, 29 (01) :51-59

[8] Multiresolution gray-scale and rotation invariant texture classification with local binary patterns [J].

Ojala, T ;

Pietikäinen, M ;

Mäenpää, T .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (07) :971-987

[9] Spatial surface coarseness analysis: technique for fingerprint spoof detection [J].

Pereira, L. F. A. ;

Pinheiro, H. N. B. ;

Cavalcanti, G. D. C. ;

Ren, Tsang Ing .

ELECTRONICS LETTERS, 2013, 49 (04) :260-261

[10] Spoofing protection for fingerprint scanner by fusing ridge signal and valley noise [J].

Tan, Bozhao ;

Schuckers, Stephanie .

PATTERN RECOGNITION, 2010, 43 (08) :2845-2857

← 1 2 →