Title :
On-line signature verification based on correlation image
Author :
Deng, Hao-ran ; Wang, Yun-Hong
Author_Institution :
Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China
Abstract :
In this paper we proposed a novel method for signature verification. Different from the conventional approaches, we suppose the sample points of the signature have some kind of correlation with each other, and the correlations contain the habitual features of the signature, which can be used to confirm the identity of the signer. In the proposed method, we first generate the matrix of the correlations of the sample points of the signature and convert the matrix into an intensity image, then use image matching approach to verify signature. The proposed method is validated on the SVC 2004 database and inspiring results are obtained.
Keywords :
correlation methods; handwriting recognition; image matching; matrix algebra; correlation image; correlation matrix; handwritten signature; image intensity; image matching; online signature verification; signature feature; Cybernetics; Handwriting recognition; Machine learning; Biometrics; Correlation Matrix; Intensity Image; LBP; On-Line Signature; SIFT; Verification;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212279