期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2015
卷号：21
期号：3
页码：123-125
DOI：10.14445/22312803/IJCTT-V21P123
出版社：Seventh Sense Research Group
摘要：As signature is generally used as a means of individual verification, there is a need for an automatic verification system. Signatures provide a safe means of verification and authorization in authorized documents. However one of the key challenges is the ability of the system to detect skilled and unskilled forgery. Many cases of bank cheque forgeries have been reported. Most of the offline signature verification system adopts recognition based technique where the system classifies a given signature sample as one of the samples from the database. However detection of a forgery in a given sample is challenging as the input sample looks alike to one of the samples in the database. A simple and a consistent system has to be designed which should identify various types of forgeries. Various approaches have been used to implement biometric signature verification some of which are dynamic time warping (DTW), Bayesian Learning, Template Matching Technique, Hidden Markov Model (HMM), Support Vector Machine (SVM) etc. This paper presents a comparative and qualitative study of these methods used for offline signature verification.
关键词：Skilled and Unskilled Forgery; SignatureVerification; Forgery detection; Dynamic Time Warping; Bayesian Learning; Template Matching Technique; HiddenMarkov Model (HMM); Support Vector Machine (SVM).
