A SVM-based method for the estimation of fingerprint and palmprint orientation

Author

Yanping Wu ; Tong Zhao ; Shuguang Wang ; Yong A ; Tiande Guo

Author_Institution

Sch. of Comput. & Control Eng., Grad. Univ. of Chinese Acad. of Sci., Beijing, China

fYear

2013

fDate

9-11 June 2013

Firstpage

343

Lastpage

348

Abstract

A SVM-based method is proposed in this paper, which is the first time that SVM is applied to the estimation of fingerprint and palmprint orientation, to the best of our knowledge. The orientation estimation problem can be regarded as a multi-classification problem by dividing the range [0 180] into 8 segments uniformly, which allows the introduction of classification methods and does not reduce the performance. In addition to the direct presentation of the estimated orientation, the rates of accuracy and recall of the minutiae are considered as statistical evaluation indexes of the performance to compare our method with the gradient-based method. Detailed analytical and experimental results are given to verify the feasibility and efficiency of our method.

Keywords

fingerprint identification; gradient methods; image classification; palmprint recognition; statistical analysis; support vector machines; SVM-based method; fingerprint orientation estimation; gradient-based method; multiclassification problem; palmprint orientation estimation; statistical evaluation indexes; Accuracy; Estimation; Fingerprint recognition; Mathematical model; Support vector machines; Testing; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4673-6248-1

Type

conf

DOI

10.1109/ICICIP.2013.6568095

Filename

6568095