The impact of visual and blind signing on signature biometrics
| Autor: | Yasemin Bay, Meryem Erbilek, Ama Fosuah Gyasi Cyprus, Erbug Celebi |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Information retrieval
Data collection Biometrics Computer science media_common.quotation_subject Feature extraction 020206 networking & telecommunications 02 engineering and technology Signature (logic) Visualization Identification (information) 0202 electrical engineering electronic engineering information engineering Identity (object-oriented programming) 020201 artificial intelligence & image processing Imitation media_common |
| Zdroj: | 2017 9th International Conference on Computational Intelligence and Communication Networks (CICN). |
| DOI: | 10.1109/cicn.2017.8319377 |
| Popis: | The ubiquitous nature of our digital lifestyle raised many security issues including signature imitation and stealing of our identity. Therefore, there is a need for robust systems to verify or identify the signatory. In this paper, in contradistinction to other researchers working in signature biometrics, we investigate and explore the impact of blind and visual signing in signature biometrics for online signature identification. Experimental performance evaluation, using the publicly available SUSIG signature database, is carried out to provide some new and preliminary insights into the relationship between different practical factors, in particular clarifying the impact on identification performance of the blind and visual signing data collection protocols used to support the signature processing. Our results explored that adaption of the blind or visual signing data collection protocols has impact on the recognition performance less critical than hitherto expected. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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