Writer-independent off-line handwritten signature verification based on real adaboost

Author

Hu, Juan ; Chen, Youbin

Author_Institution

Grad. Sch. at Shenzhen, Tsinghua Univ., Shenzhen, China

fYear

2011

fDate

8-10 Aug. 2011

Firstpage

6095

Lastpage

6098

Abstract

A method for writer-independent off-line handwritten signature verification based on grey level feature extraction and Real Adaboost algorithm is proposed. Firstly, both global and local features are used simultaneously. Secondly, dissimilarity vector is adopted. Finally, Real Adaboost algorithm is applied. Experiments on the public signature database GPDS Corpus show that our proposed method has achieved the FRR 5.64% and the FAR 5.37% which are the best so far compared with other published results.

Keywords

authorisation; feature extraction; grey systems; handwriting recognition; pattern classification; vectors; dissimilarity vector; grey level feature extraction; public signature database GPDS corpus; real Adaboost algorithm; writer-independent off-line handwritten signature verification; Databases; Feature extraction; Forgery; Support vector machine classification; Testing; dissimilarity vector; grey level features; off-line handwritten signature verification; real Adaboost; writer-independent;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on

Conference_Location

Deng Leng

Print_ISBN

978-1-4577-0535-9

Type

conf

DOI

10.1109/AIMSEC.2011.6010102

Filename

6010102