Method of fingerprint and voiceprint based decision level fusion recognition

Jianwu ZHANG; Jiajia YANG; Zhendong WU

doi:10.11959/j.issn.1000-0801.2018130

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Method of fingerprint and voiceprint based decision level fusion recognition

Topic:Cyberspace Security | 更新时间：2024-06-05

- Method of fingerprint and voiceprint based decision level fusion recognition
- Telecommunications Science Vol. 34, Issue 3, Pages: 32-40(2018)
- 作者机构：
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- DOI：10.11959/j.issn.1000-0801.2018130
  CLC： TP301
- Published Online：2018-03，
  
  Published：20 March 2018
- 稿件说明：
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Jianwu ZHANG, Jiajia YANG, Zhendong WU. Method of fingerprint and voiceprint based decision level fusion recognition[J]. Telecommunications science, 2018, 34(3): 32-40.
DOI：

Jianwu ZHANG, Jiajia YANG, Zhendong WU. Method of fingerprint and voiceprint based decision level fusion recognition[J]. Telecommunications science, 2018, 34(3): 32-40. DOI： 10.11959/j.issn.1000-0801.2018130.

摘要

结合指纹和声纹在识别环境中的优良互补性以及两种特征相关性不强的特点，提出一种基于指纹和声纹决策级融合识别方法。在对相应的指纹和声纹分别提取特征和识别之后，使用提出的二次比较选择模型（second comparison of choosing model

SCCM）在决策层上利用分数层数据信息进行辅助分类，根据类别判断是否启用声纹识别，使得双模态融合系统平均数据处理量降低了32.8%。基于FVC2002DB1指纹库和自采集声纹库进行了实验验证。实验结果显示，多模态融合可以有效解决单模态的识别限制，识别率相对单模态提升了将近5.08%和4.60%，且稳定性较高。

Abstract

Because of strong complementarity in the recognition environment and the low correlation characteristics of the two features

a fingerprint and voiceprint based decision level fusion recognition method was proposed.After extracting the features and recognition of corresponding fingerprint and voiceprint

the second comparison of choosing model (SCCM) was used to classify at the decision-making level and judge whether to enable voiceprint recognition according to the category

reduced the average data processing volume of the dual-mode fushion system by 32.8%.Experiments applied to FVC2002DB1 fingerprint library and self-collecting voiceprint library.The experimental results show that the multi-biometrics fusion effectively solves the single-modal recognition limitation and the recognition rate improves nearly 5.08% and 4.60% as well as get a more stable system.

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references

WILD P , RADU P , CHEN L L , et al . Robust multimodal face and fingerprint fusion in the presence of spoofing attacks [J ] . Pattern Recognition , 2016 ( 50 ): 17 - 25 .

MAI G C , LIM M H , YUEN P C . Binary feature fusion for discriminative and secure multi-biometric cryptosystem [J ] . Image and Vision Computing , 2017 ( 58 ): 254 - 265 .

BRUNELLI R , FALAVINGA D . Person indentification using multiple cues [J ] . IEEE Transcations on Pattern Analysis and Machine Intelligence , 1995 , 17 ( 10 ): 985 - 966 .

PRABHAKAR S , JAIN A K . Decision-level fusion in fingerprint verification [J ] . Pattern Recognition , 2002 , 35 ( 4 ): 861 - 874 .

CONTI V , MILITELLO C , SORBELLO F , et al . A frequency-based approach for features fusion in fingerprint and iris multimodal biometric identification systems [J ] . IEEE Transactions on Systems Man ＆ Cybernetics Part C , 2010 , 40 ( 4 ): 384 - 395 .

LEE H C , GAENSSLEN R E . Advances in fingerprint technology [M ] . Amsterdam : Elsevier 2001 .

MEI Y , ZHAO B , ZHOU Y , et al . Orthogonal curved-line Gabor filter for fast fingerprint enhancement [J ] . Electronics Letters , 2014 , 50 ( 3 ): 175 - 177 .

WANG Q J . Face recognition based on Log-Gabor and orthogonal Iso projection [J ] . Computer Science , 2011 .

DYRE S , SUMATHI C P . Hybrid approach to enhancing fingerprint images using filters in the frequency domain [C ] // IEEE International Conference on Computational Intelligence and Computing Research , Dec 10 - 12 , 2015 , Madurai,India.Piscataway : IEEE Press , 2015 : 1 - 6 .

NAKAJIMA H , KOBAYASHI K , MORIKAWA M , et al . A fingerprint matching technique based on phase-only correlation [J ] . IEEE Transactions on Sensors ＆ Micromachines , 2006 , 126 ( 2 ): 38 - 46 .

CALIFANO A , COLVILLE S E , GERMAIN R S . Method and apparatus for fingerprint matching using transformation parameter clustering based on local feature correspondences:US,US 6041133 A [P ] . 2000 .

RAITIO T , SUNI A , YAMAGISHI J , et al . HMM-based speech synthesis utilizing glottal inverse filtering [J ] . IEEE Transactions on Audio Speech ＆ Language Processing , 2011 , 19 ( 1 ): 153 - 165 .

DEY N S , MOHANTY R , CHUGH K L . Speech and speaker recognition system using artificial neural networks and hidden markov model [C ] // International Conference on Communication Systems and Network Technologies , May 11 - 13 , 2012 , Washington,USA.Piscataway : IEEE Press , 2012 : 311 - 315 .

SU D , WU X , XU L . GMM-HMM acoustic model training by a two level procedure with Gaussian components determined by automatic model selection [C ] // IEEE International Conference on Acoustics Speech and Signal Processing , March 14 - 19 , 2010 , Dallas,USA.Piscataway : IEEE Press , 2010 : 4890 - 4893 .

WANG K J , SONG X J , WANG C H . Research on decision level fusion algorithm by fusing hand geometry and palmprint [J ] . Journal of Engineering of Heilongjiang University , 2010 .

VEERAMACHANENI K , OSADCIW L , ROSS A , et al . Decision-level fusion strategies for correlated biometric classifiers [C ] // IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops , 2008 , June 24 - 26 , 2008 , Anchorage,USA.Piscataway : IEEE Press , 2008 : 1 - 6 .

SHEN L , JI Z , LI Y , et al . Coding Gabor features for multi-modal biometrics [C ] // 2010 Chinese Conference on Pattern Recognition , Oct 20 - 33 , 2010 , Chongqing,China.Piscataway : IEEE Press , 2010 : 1 - 4 .

李昊，傅曦 . 物联网指纹识别系统算法及实现（Visual C++） [M ] . 北京：人民邮电出版社 2011 .

LI H , FU X . Fingerprinting system algorithms and implementation(visual C++) [M ] . Beijing : Posts＆Telecom Press 2011 .

ABRAHAM J , KWAN P , GAO J B . Fingerprint matching using a hybrid shape and orientation descriptor [J ] . State of the Art in Biometrics , 2011 : 25 - 26 .

REYNOLDS D A , QUATIERI T F , DUNN R B . Speaker verification using adapted Gaussian mixture models [J ] . Digital Signal Processing , 2000 , 10 ( 1 ): 19 - 41 .

陈前 . 人脸与虹膜在特征层融合识别的研究 [D ] . 长春：吉林大学 2012 .

CHEN Q . Research on fusion recognition of face and iris in feature layer [D ] . Changchun : Jilin University 2012 .

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