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
收藏
页码:43 / 48
页数:6
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