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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pal, S. Chanda, S. Pal, U. Franke, K. Blumenstein, M. |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Information and Communication Technology, Griffith University, Gold Coast Australia (Pal, S.; Blumenstein, M.) || Department of Computer Science and Media Technology, Gøvik University College, Norway (Chanda, S.; Franke, K.) || Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India (Pal, U.) |
| Abstract | In the field of biometric authentication, automatic signature identification and verification has been a strong research area because of the social and legal acceptance and extensive use of the written signature as an easy method for authentication. Signature verification is a process in which the questioned signature is examined in detail in order to determine whether it belongs to the claimed person or not. Signatures provide a secure means for confirmation and authorization in legal documents. So nowadays, signature identification and verification becomes an essential component in automating the rapid processing of documents containing embedded signatures. Sometimes, part-based signature verification can be useful when a questioned signature has lost its original shape due to inferior scanning quality. In order to address the above-mentioned adverse scenario, we propose a new feature encoding technique. This feature encoding is based on the amalgamation of Gabor filter-based features with SURF features (G-SURF). Features generated from a signature are applied to a Support Vector Machine (SVM) classifier. For experimentation, 1500 (50×30) forgeries and 1200 (50×24) genuine signatures from the GPDS signature database were used. A verification accuracy of 97.05% was obtained from the experiments. |
| Starting Page | 586 |
| Ending Page | 591 |
| File Size | 743764 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467351171 |
| ISSN | 21647143 |
| e-ISBN | 9781467351195 |
| DOI | 10.1109/ISDA.2012.6416603 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-11-27 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Decision support systems SURF Off-line system Conferences Part-based character recognition Document Analysis Rail to rail outputs Support Vector Machine Intelligent systems Signature Verification |
| Content Type | Text |
| Resource Type | Article |
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