TY - GEN
T1 - Off-line signature verification based on combination of modified direction and microstructure features
AU - Yang, Danfeng
AU - Qin, Yuzhu
AU - Huang, Zhimin
AU - Lu, Yue
PY - 2011
Y1 - 2011
N2 - Off-line signature verification is an important form of behavioral biometric identification. We present a method utilizing Modified Direction Feature(MDF) and Microstructure Feature(MSF) to tackle the problem. MDF and MSF belong to geometric structure features, but these two features are different from each other in each emphasis. In our study, global information in signatures' boundaries is represented by MDF, while local information is represented by MSF. In order to get features with lower dimensions, principal component analysis is employed to reduce redundant dimensions. In addition, we adopt support vector machine as classifier for verification process. The proposed strategy is evaluated on the GPDS and MCYT corpora. Experimental results have demonstrated that the proposed method is effective to improve off-line signature verification accuracy.
AB - Off-line signature verification is an important form of behavioral biometric identification. We present a method utilizing Modified Direction Feature(MDF) and Microstructure Feature(MSF) to tackle the problem. MDF and MSF belong to geometric structure features, but these two features are different from each other in each emphasis. In our study, global information in signatures' boundaries is represented by MDF, while local information is represented by MSF. In order to get features with lower dimensions, principal component analysis is employed to reduce redundant dimensions. In addition, we adopt support vector machine as classifier for verification process. The proposed strategy is evaluated on the GPDS and MCYT corpora. Experimental results have demonstrated that the proposed method is effective to improve off-line signature verification accuracy.
KW - Combination
KW - Microstructure Feature
KW - Modified Direction Feature
KW - Off-line Signature Verification
KW - Support Vector Machine
UR - https://www.scopus.com/pages/publications/84855378321
U2 - 10.1007/978-3-642-27183-0_29
DO - 10.1007/978-3-642-27183-0_29
M3 - 会议稿件
AN - SCOPUS:84855378321
SN - 9783642271823
T3 - Communications in Computer and Information Science
SP - 270
EP - 279
BT - Signal Processing, Image Processing and Pattern Recognition - Int. Conf., SIP 2011, Held as Part of the Future Generation Information Technology Conf., FGIT 2011, in Conjunction with GDC 2011, Proc.
T2 - 2011 International Conference on Signal Processing, Image Processing and Pattern Recognition, SIP 2011, Held as Part of the 3rd International Mega-Conference on Future-Generation Information Technology, FGIT 2011, in Conjunction with GDC 2011
Y2 - 8 December 2011 through 10 December 2011
ER -