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http://hdl.handle.net/10603/258604
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Robust Multimodal Biometric Recognition System using Hand Geometry and Iris Features | |
dc.date.accessioned | 2019-09-19T04:53:11Z | - |
dc.date.available | 2019-09-19T04:53:11Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/258604 | - |
dc.description.abstract | Biometric recognition and identification evolves as an inevitable process while ensuring Security and Privacy of deeds of an individual while being a part of e-transactions. The Internet and its infrastructure has progressed substantially in the recent times so as to complete tasks easier and smarter across many fields in daily routine. Unlike passwords, biometric authentication process is accountable, robust, reliable and less time consuming. Despite benefits, owing to the modern day technical advancements and threats unimodal biometric authentication systems cannot endure its underlying motive. The average identification time of available biometric authentication systems to process a well-captured biometric modality is measured less than 5 seconds which is more than enough for a hacking system to tamper and steal the transferred trait. Moreover, the way it verifies the biometric modality causes more damage than the time taken to accomplish the authentication test. In both the cases, a biometric theft leads to arduous effect than a password newlinetheft since passwords are user-defined and trivial whereas biometric traits are physically associated to an individual which is ultimate. It urges to propose a multi-modal biometric authentication system since the unimodal systems can no longer defend masquerading attack. As it becomes mandate to transfer the traits to claim authentication, it is high-time to find an alternate way of communicating the biometric traits from the traditional methods. newline newline | |
dc.format.extent | xvii, 112p. | |
dc.language | English | |
dc.relation | p.102-111 | |
dc.rights | university | |
dc.title | Robust multimodal biometric recognition system using hand geometry and iris features | |
dc.title.alternative | ||
dc.creator.researcher | Velmurugan S | |
dc.subject.keyword | Biometric Recognition | |
dc.subject.keyword | Engineering and Technology,Computer Science,Computer Science Interdisciplinary Applications | |
dc.subject.keyword | Hand Geometry and Iris Features | |
dc.subject.keyword | Robust Multimodal | |
dc.description.note | ||
dc.contributor.guide | Selvarajan S | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Electrical Engineering | |
dc.date.registered | n.d. | |
dc.date.completed | 2018 | |
dc.date.awarded | 31/12/2018 | |
dc.format.dimensions | 21 cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Electrical Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 9.63 kB | Adobe PDF | View/Open |
02_certificates.pdf | 786.61 kB | Adobe PDF | View/Open | |
03_abstract.pdf | 9.36 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 5.04 kB | Adobe PDF | View/Open | |
05_table_of_contents.pdf | 141.69 kB | Adobe PDF | View/Open | |
06_list_of_symbols_and_abbreviations.pdf | 9.56 kB | Adobe PDF | View/Open | |
07_chapter1.pdf | 120.98 kB | Adobe PDF | View/Open | |
08_chapter2.pdf | 156.55 kB | Adobe PDF | View/Open | |
09_chapter3.pdf | 368.12 kB | Adobe PDF | View/Open | |
10_chapter4.pdf | 499.13 kB | Adobe PDF | View/Open | |
11_conclusion.pdf | 78 kB | Adobe PDF | View/Open | |
12_references.pdf | 94.6 kB | Adobe PDF | View/Open | |
13_list_of_publications.pdf | 62.83 kB | Adobe PDF | View/Open |
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