Title :
A neural network approach for off-line signature verification
Author :
Ng Geok See ; Ong Hee Seng
Author_Institution :
Div. of Comput. Technol., Nanyang Technol. Univ., Singapore
Abstract :
We describe methods to analyse and obtain the optimal values of various factors that affect the performance of a signature verification system using a neural network approach. A modified model of backpropagation is used to reduce the learning time of the system. Various factors that are examined in this paper are the effect of learning rate of the neural network, effect of skilled forgeries (computer generated), and effect of preprocessing of images on the accuracy of the system.<>
Keywords :
backpropagation; biometrics (access control); neural nets; optical character recognition; backpropagation; image preprocessing; learning rate; learning time; neural network approach; offline signature verification; system accuracy; Acceleration; Authorization; Computer networks; Forgery; Handwriting recognition; Neural networks; Performance analysis; Pixel; Shape; System testing;
Conference_Titel :
TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on
Conference_Location :
Beijing, China
Print_ISBN :
0-7803-1233-3
DOI :
10.1109/TENCON.1993.320127
