Title :
Off-Line Signature Verification Using Graphical Model
Author :
Lv, Hairong ; Bai, Xinxin ; Yin, Wenjun ; Dong, Jin
Author_Institution :
IBM China Res. Lab., Beijing, China
Abstract :
In this paper, we propose a novel probabilistic graphical model to address the off-line signature verification problem. Different from previous work, our approach introduces the concept of feature roles according to their distribution in genuine and forgery signatures, with all these features represented by a unique graphical model. And we propose several new techniques to improve the performance of the new signature verification system. Results based on 200 persons´ signatures (16000 signature samples) indicate that the proposed method outperforms other popular techniques for off-line signature verification with a great improvement.
Keywords :
handwriting recognition; feature roles; forgery signatures; genuine signatures; offline signature verification; probabilistic graphical model; Forgery; Graphical models; Hidden Markov models; Probabilistic logic; Training; graphical model; signature verification;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.922