Research Article
Article:Invariant features comparison in hidden markov model and SIFT for offline handwritten signature database
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 2 - Issue 7 |
| Published: June 2010 |
| Authors: Neeraj Shukla, Dr. Madhu Shandilya |
10.5120/678-953
|
Neeraj Shukla, Dr. Madhu Shandilya . Article:Invariant features comparison in hidden markov model and SIFT for offline handwritten signature database. International Journal of Computer Applications. 2, 7 (June 2010), 31-34. DOI=10.5120/678-953
@article{ 10.5120/678-953,
author = { Neeraj Shukla,Dr. Madhu Shandilya },
title = { Article:Invariant features comparison in hidden markov model and SIFT for offline handwritten signature database },
journal = { International Journal of Computer Applications },
year = { 2010 },
volume = { 2 },
number = { 7 },
pages = { 31-34 },
doi = { 10.5120/678-953 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2010
%A Neeraj Shukla
%A Dr. Madhu Shandilya
%T Article:Invariant features comparison in hidden markov model and SIFT for offline handwritten signature database%T
%J International Journal of Computer Applications
%V 2
%N 7
%P 31-34
%R 10.5120/678-953
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In Handwritten signatures analyzed for forgery have to undergo feature extraction process, due to varied samples in size rotation and intra-domain changes, invariance has to be achieved during feature extraction process; circular Hidden Markov Model with discrete radon transform approach of feature extraction provides invariance. On other hand Scale Invariant Feature Transform (SIFT) has inherent invariant feature extraction approach. This paper compares both approaches on common signature databases for False acceptance rate(FAR),False Rejection Rate(FRR) and Equal Error Rate(EER)
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