Mendeley
TY  _  JOUR
ID  -  13940904125437534
TI  -  Online Signature Verification in Stationary Wavelet Transform Domain
JO  -  Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran
JA  -  ES
LA  -  fa
SN  -  16823745
AU  -  Valizadeh M.
AU  -  Kabir E.
AD  -  دانشگاه تربیت مدرس
AD  -  دانشگاه تربیت مدرس
Y1  -  2010
PY  -  2010
VL  -  1
IS  -  
SP  -  31
EP  -  39
KW  -  Extended regression
extreme point
stationary wavelet transform
online signature verification
skilled forgery
DO  -  
N2  -  In this paper, an online signature verification method using extended regression in stationary wavelet domain is presented. To calculate the similarity between two signatures by extended regression, we should equalize the time length of the corresponding signals in two signatures. Using all points of the signals to equalize their time length will decrease the difference between a genuine signature and its forgery. Here a new approach based on the extreme points warping of the signals is presented. This approach equalizes the time length of two signals without degrading the differences between them. Also we calculated the similarity of signatures by using the details of the signals in stationary wavelet transform, SWT, domain, which showed very good results. 
The proposed system was tested on SVC2004 signature database. The results were compared with the results of participant teams in the first international signature verification competition. We have gained EER=6% for skilled forgery signatures. Comparing the result, it shows that we stand in the second rank between all the participants. This system has no verification error for random forgery signatures and stands in the first rank. Our experimental results show that using SWT domain instead of time domain decreases the verification error rate by 35%.
UR  - rimag.ir/en/Article/27969
L1  - rimag.ir/en/Article/Download/27969
ER  -  
