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Improved Offline Signature Verification Scheme Using Feature Point Extraction Method
| Content Provider | NIT Rourkela |
|---|---|
| Author | Jena, D. Majhi, B. Panigrahy, S. K. Jena, S. K. |
| Description | 7th IEEE International Conference on Cognitive Informatics (ICCI 2008), 2008. |
| Abstract | In this paper a novel offline signature verification scheme has been proposed. The scheme is based on selecting 60 feature points from the geometric centre of the signature and compares them with the already trained feature points. The classification of the feature points utilizes statistical parameters like mean and variance. The suggested scheme discriminates between two types of originals and forged signatures. The method takes care of skill, simple and random forgeries. The objective of the work is to reduce the two vital parameters False Acceptance Rate (FAR) and False Rejection Rate (FRR) normally used in any signature verification scheme. In the end comparative analysis has been made with standard existing schemes. |
| File Size | 703499 |
| File Format | |
| ISBN | 9781424425389 |
| DOI | 10.1109/COGINF.2008.4639204 |
| Language | English |
| Publisher | IEEE Xplore |
| Access Restriction | Open |
| Subject Keyword | Offline signature Geometric centre Feature point Forgeries Euclidean Distance Model FAR (False Acceptance Rate) FRR (False Rejection Rate) |
| Content Type | Text |
| Resource Type | Article |
