Title :
A comparative study of the recent trends in biometric signature verification
Author :
Zareen, Farhana Javed ; Jabin, Suraiya
Author_Institution :
Dept. of Comput. Sci., Jamia Millia Islamia, New Delhi, India
Abstract :
Signature verification is a widely and commonly accepted practice for authentication of an individual. Whereas off-line signature verification contributes very less to accurate identification, on-line signature verification has been successfully implemented in recent researches to achieve 80%-98% of accuracy. Various approaches have been used to implement biometric signature recognition some of which are dynamic time warping (DTW), Bayesian Learning, Hidden Markov model (HMM), Neural Networks, Support Vector machine (SVM) etc. This paper presents a comparative and qualitative study of these methods used for biometric signature verification.
Keywords :
belief networks; handwriting recognition; hidden Markov models; learning (artificial intelligence); neural nets; support vector machines; Bayesian learning approach; DTW approach; HMM approach; biometric signature verification; dynamic time warping approach; hidden Markov model approach; neural networks approach; offline signature verification; online signature verification; support vector machine approach; Artificial neural networks; Bayes methods; Handwriting recognition; Hidden Markov models; Support vector machines; Bayesian Learning; Biometric; DTW; HMM; Neural Networks; SVM; Signature Verification;
Conference_Titel :
Contemporary Computing (IC3), 2013 Sixth International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-0190-6
DOI :
10.1109/IC3.2013.6612219
