Multimodal Biometric Recognition System Using Feature Level Fusion

被引：0

作者：

Rane, Milind E. ^{[1
]}

Deshpande, Prameya P. ^{[1
]}

机构：

[1] Vishwakarma Inst Technol, Dept Elect Engn, Pune, Maharashtra, India

来源：

2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA) | 2018年

关键词：

Face; Palmprint; Biometric recognition; SSIM; Feature level fusion; SVM; Gabor; Radon; Ridgelet; Radon-Gabor;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With so many recent advancements in security, there is no doubt that biometric recognition will take over everything. This paper is to list a few ways of combining multiple biometric modals using fusion. The paper mainly focuses on multiple processes used for feature extraction from face and palmprint. FACE 94, 95 and 96[1] are face databases and IITD palmprint database is used for palm. The features were extracted using various methods like Gabor, Radon, Ridgelet and Radon-Gabor. Feature level fusion was applied using algorithms like Mean, weighted average. For the classification SVM classifier was used. Another method used for classification was confidence based similarity checking using SSIM.

引用

页数：5

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