Multimodal Biometric Fusion Approach Based on Iris and Face

王风华; 韩九强; 姚向华

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Multimodal Biometric Fusion Approach Based on Iris and Face

更新时间：2025-12-08

- Multimodal Biometric Fusion Approach Based on Iris and Face
- Vol. 42, Issue 2, Pages: 133-137(2008)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Online First：10 February 2008，
  
  Published：2008
- 稿件说明：
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王风华, 韩九强, 姚向华. Multimodal Biometric Fusion Approach Based on Iris and Face[J]. 2008, 42(2): 133-137.
DOI：

王风华, 韩九强, 姚向华. Multimodal Biometric Fusion Approach Based on Iris and Face[J]. 2008, 42(2): 133-137. DOI：

摘要

针对单一生物特征识别方法易受干扰、应用受限制等问题

提出了一种基于虹膜和人脸的多生物特征融合方法以提高身份识别的精度及可靠性.该融合方法利用Log-Gabor相位编码算法和Laplacianfaces算法对虹膜和人脸进行特征提取及匹配

然后在匹配层对两种生物特征的匹配得分值使用最小最大概率机策略进行融合

最后利用融合后得分值进行决策.该方法与单生物特征识别方法相比

识别性能明显提高.在UBIRIS虹膜库和ORL人脸库构成的多模生物特征库中进行了测试

实验结果表明:该方法的等错误率可降低到0.28%

比单一虹膜和单一人脸方法分别降低了0.69%和1.62%

与采用传统融合策略的方法相比

等错误率也降低了0.2%以上.

Abstract

The recognition performance of the single biometric system is easily affected by the surrounding environment. In order to improve the recognition reliability

a multimodal biometric fusion approach based on iris and face was proposed. In the proposed approach

the iris is processed using the phase information algorithm based on Log-Gabor filtering and the face is processed using Laplacianfaces algorithm. The two matching scores obtained from iris and face are fused using the minimax probability machine fusion strategy

and the fused matching score is used to make the final decision. The performance of the proposed approach is obviously improved. The experimental results in a multimodal database

which consists of UBIRIS iris database and ORL face database

show that the equal error rate of the proposed approach is 0.28%

which decreases 0.69% and 1.62%

respectively compared with both the single biometric approaches and decreases over 0.2% compared to the tradition fusion strategies.

关键词

Keywords

references

ROSS A, JAIN A K. Information fusion in biometrics [J]. Pattern Recognition Letters, 2003,24(13): 2115-2125.

LIU Zongyi, SARKAR S. Outdoor recognition at a distance by fusing gait and face [J]. Image Vision Computing, 2007,25(6):817-832.

DAUGMAN J G. How iris recognition works [J]. IEEE Transaction on Circuits and Systems for Video Technology, 2004,14(1): 21-30.

DU Yingzi. Using 2D Log-Gabor spatial filters for iris recognition[C/CD]∥ Biometric Technology for Human Identification: III. Bellingham,USA: International Society for Optical Engineering, 2006:6202F.

HE Xiaofei,YAN Shuicheng, HU Yuxiao, et al. Face recognition using Laplacianfaces [J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 2005,27(3):328-340.

LANCKRIET G R G, EI G L, BHATTACHARYYA C, et al. Minimax probability machine [C]∥Proceedings of Advances in Neural Information Processing Systems. Berkeley,USA: Department of EECS University of California, 2002: 1-7.

PROENCA H, ALEXANDRE L A. UBIRIS iris image database [DB/OL].(2005-05-01)[2006-03-12].http:∥iris.di.ubi.pt.

ATT Laboratories Cambridge. The ORL database of faces [DB/OL].(1999-03-02)[2006-11-08].http:∥www.cam-orl.co.uk/facedatabase.html.

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