Hand Biometric Recognition Based on Fused Hand Geometry and Vascular Patterns
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, GiTae | - |
dc.contributor.author | Kim, Soowon | - |
dc.date.accessioned | 2021-09-06T04:00:33Z | - |
dc.date.available | 2021-09-06T04:00:33Z | - |
dc.date.created | 2021-06-14 | - |
dc.date.issued | 2013-03 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/103877 | - |
dc.description.abstract | A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | VEIN | - |
dc.title | Hand Biometric Recognition Based on Fused Hand Geometry and Vascular Patterns | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Soowon | - |
dc.identifier.doi | 10.3390/s130302895 | - |
dc.identifier.wosid | 000316612900014 | - |
dc.identifier.bibliographicCitation | SENSORS, v.13, no.3, pp.2895 - 2910 | - |
dc.relation.isPartOf | SENSORS | - |
dc.citation.title | SENSORS | - |
dc.citation.volume | 13 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 2895 | - |
dc.citation.endPage | 2910 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.subject.keywordPlus | VEIN | - |
dc.subject.keywordAuthor | multimodal biometric | - |
dc.subject.keywordAuthor | hand biometric | - |
dc.subject.keywordAuthor | hand geometry | - |
dc.subject.keywordAuthor | vascular-pattern recognition | - |
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