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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | VEIN BIOMETRIC AUTHENTICATION USING ANDROID APPLICATION |
| Authors Name: | Aswathy S Nair , Anila K Prince , Arsha Suhrdy D , Rahanaz Habeeb |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_199509
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| Published Paper Id: | IJNRD2306339 |
| Published In: | Volume 8 Issue 6, June-2023 |
| DOI: | |
| Abstract: | Human recognition on smartphone devices for unlocking, online payment, and bank account verification is one of the significant uses of biometrics. The exponential development and integration of this technology have been established since the introduction in 2013 of the fingerprints mounted sensor in the Apple iPhone 5s by Apple Inc.c (MotorolacAtrix was previously launched in 2011). Nowadays, in the commercial world, the main biometric variants integrated into mobile devices are fingerprint, facial, iris, and voice. In 2019, LGc Electronics announced the mobile exhibiting vascular biometric recognition, integrated using the palm vein modality: LGc G8 ThinQ(hand ID). In this work, in an attempt to become the become the first research-embedded approach to smartphone vein identification, a novel wrist vascular biometric recognition is designed, implemented, and tested on the Xiaomi Pocophone F1 and the Xiaomic Mi 8 devices. The near- infrared camera mounted for facial recognition on these devices accounts for the hardware employed. Two software algorithms, TGS-CVBR R and PIS- CVBR R, are designed and applied to a database generation and the identification task, respectively. The database, named UC3M-Contactless Version 2 (UC3M-CV2), consists of 2400 contactless infrared images from both wrists of 50 different subjects (25 females and 25 males, 100 individual wrists in total), collected in two separate sessions with different environmental light environmental light conditions. The vein biometric recognition, using PIS-CVBR , is based on the SIFT R, SURF R, and ORB algorithms. |
| Keywords: | Vein biometric recognition ,android application ,wrist vascular biometric recognition ,contacless vascular biometric recognition , near-infrared camera ,SIFT ,SURF. |
| Cite Article: | "VEIN BIOMETRIC AUTHENTICATION USING ANDROID APPLICATION", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 6, page no.d398-d403, June-2023, Available :http://www.ijnrd.org/papers/IJNRD2306339.pdf |
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2306339 Registration ID: 199509 Published In: Volume 8 Issue 6, June-2023 DOI (Digital Object Identifier): Page No: d398-d403 Country: Pathanamthitta, KERALA, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2306339 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2306339 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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