Biometric Identifier Based on Hand and Hand-Written Signature Contour Information

被引：0

作者：

Pitters-Figueroa, Fernando A. ^{[1
]}

Travieso, Carlos M. ^{[1
]}

Dutta, Malay Kishore ^{[2
]}

Singh, Anushikha ^{[2
]}

机构：

[1] Univ Las Palmas Gran Canaria, IDETIC, Signals & Commun Dept, Las Palmas Gran Canaria, Spain

[2] Amity Univ, Dept Elect & Commun Engn, Noida, India

来源：

2017 TENTH INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING (IC3) | 2017年

关键词：

biometrics; identification; hand shape; handwritten signature; classification; pattern recognition; MODELS;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The present work presents a biometric identifier system using the combination of two different features: hands shape (finger lengths and width) and hand-written signature contour. Signature database contains 300 different signers with 24 signatures and the hand database has 144 owners with 10 images. The study covers three different classifiers: Hidden Markov Models (HMM), Support Vector Machines (SVM) and a combination of both using the Fisher Kernel. Systems are evaluated separately and in conjunction, giving in each case 100% of identification success rate for the combined classifier. The combination of features gives better results when reducing the training set than the independent systems.

引用

页码：43 / 48

页数：6

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