Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/258604
Full metadata record
DC FieldValueLanguage
dc.coverage.spatialRobust Multimodal Biometric Recognition System using Hand Geometry and Iris Features
dc.date.accessioned2019-09-19T04:53:11Z-
dc.date.available2019-09-19T04:53:11Z-
dc.identifier.urihttp://hdl.handle.net/10603/258604-
dc.description.abstractBiometric 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.extentxvii, 112p.
dc.languageEnglish
dc.relationp.102-111
dc.rightsuniversity
dc.titleRobust multimodal biometric recognition system using hand geometry and iris features
dc.title.alternative
dc.creator.researcherVelmurugan S
dc.subject.keywordBiometric Recognition
dc.subject.keywordEngineering and Technology,Computer Science,Computer Science Interdisciplinary Applications
dc.subject.keywordHand Geometry and Iris Features
dc.subject.keywordRobust Multimodal
dc.description.note
dc.contributor.guideSelvarajan S
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Electrical Engineering
dc.date.registeredn.d.
dc.date.completed2018
dc.date.awarded31/12/2018
dc.format.dimensions21 cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Electrical Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File9.63 kBAdobe PDFView/Open
02_certificates.pdf786.61 kBAdobe PDFView/Open
03_abstract.pdf9.36 kBAdobe PDFView/Open
04_acknowledgement.pdf5.04 kBAdobe PDFView/Open
05_table_of_contents.pdf141.69 kBAdobe PDFView/Open
06_list_of_symbols_and_abbreviations.pdf9.56 kBAdobe PDFView/Open
07_chapter1.pdf120.98 kBAdobe PDFView/Open
08_chapter2.pdf156.55 kBAdobe PDFView/Open
09_chapter3.pdf368.12 kBAdobe PDFView/Open
10_chapter4.pdf499.13 kBAdobe PDFView/Open
11_conclusion.pdf78 kBAdobe PDFView/Open
12_references.pdf94.6 kBAdobe PDFView/Open
13_list_of_publications.pdf62.83 kBAdobe PDFView/Open


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: