On-line signature verification based on Gabor features

Author

Ling, Xue ; Wang, Yunhong ; Zhang, Zhaoxiang ; Wang, Yiding

Author_Institution

Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China

fYear

2010

fDate

14-15 May 2010

Firstpage

1

Lastpage

4

Abstract

In this paper, the local features obtained from the signature has been used to create the texture image based on the spatio-temporal correlation matrix. The Gabor wavelets exhibit desirable characteristics of spatial locality and orientation selectivity, and are optimally localized in the space and frequency domains. So it has been chosen to extract the Gabor features of the image. Signature is a small sample point problem and Support vector machine (SVM) is especially fit for two classes´ problem of small sample. The Gabor features vector has been imported to the SVM classifier and the classification result is obtained. The methods proposed in this paper are validated on the SVC 2004 database and inspiring results are obtained.

Keywords

Gabor filters; correlation methods; feature extraction; handwriting recognition; image classification; image texture; matrix algebra; support vector machines; wavelet transforms; Gabor features; Gabor wavelets; SVC 2004 database; SVM classifier; frequency domains; online signature verification; space domains; spatiotemporal correlation matrix; support vector machine; texture image; Acceleration; Artificial neural networks; Azimuth; Data mining; Feature extraction; Handwriting recognition; Hidden Markov models; Space technology; Support vector machine classification; Support vector machines; Gabor features; Signature verification; Support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless and Optical Communications Conference (WOCC), 2010 19th Annual

Conference_Location

Shanghai

Print_ISBN

978-1-4244-7597-1

Type

conf

DOI

10.1109/WOCC.2010.5510683

Filename

5510683