Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/39889
Full metadata record
DC FieldValueLanguage
dc.coverage.spatialHybrid model for biometrics based Human identification and recognition System using hand dorsum geometry And finger knuckle printen_US
dc.date.accessioned2015-04-30T08:21:12Z-
dc.date.available2015-04-30T08:21:12Z-
dc.date.issued2015-04-30-
dc.identifier.urihttp://hdl.handle.net/10603/39889-
dc.description.abstractThe adoption of Biometrics based Automatic Human Recognition newlineand Identification System is gaining importance and more focus Reliability in newlinethe human recognition is the key to the security Many physiological newlinecharacteristics of human biometrics are typically time invariant easy to newlineacquire and unique for every individual Biometric features such as face iris newlinefingerprint hand geometry palmprint signature etc have been suggested for newlinethe security in access control Most of the previous researches in biometrics newlinehave been focused on fingerprint and face The reliability of personal newlineidentification using face is low due to the problems of pose lighting newlineorientation and gesture Fingerprint identification is widely used in personal newlineidentification as it has worked well in most cases in the past However it is newlinedifficult to acquire fingerprint features minutiae for certain class of newlinepersons such as manual labourers elderly people etc As a result other newlinebiometric characteristics are receiving increasing attention newlineBiometric systems that operate using any single biometric newlinecharacteristic have some limitations which may lead to poor identification newlineresults due to many reasons such as noise in sensed data Intra class newlinevariations distinctiveness non universality spoof attacks etc Some of the newlinelimitations imposed by unimodel biometric systems can be overcome by using newlinemultiple biometric modalities newline newlineen_US
dc.format.extentxx, 186p.en_US
dc.languageEnglishen_US
dc.relationp172-184.en_US
dc.rightsuniversityen_US
dc.titleHybrid model for biometrics based Human identification and recognition System using hand dorsum geometry And finger knuckle printen_US
dc.title.alternativeen_US
dc.creator.researcherMathivanan Ben_US
dc.subject.keywordAutomatic Human Recognitionen_US
dc.subject.keywordmultiple biometric modalitiesen_US
dc.description.notereference p172-184.en_US
dc.contributor.guidePalanisamy Ven_US
dc.publisher.placeChennaien_US
dc.publisher.universityAnna Universityen_US
dc.publisher.institutionFaculty of Information and Communication Engineeringen_US
dc.date.registeredn.d,en_US
dc.date.completed01/12/2013en_US
dc.date.awarded30/12/2013en_US
dc.format.dimensions23cm.en_US
dc.format.accompanyingmaterialNoneen_US
dc.source.universityUniversityen_US
dc.type.degreePh.D.en_US
Appears in Departments:Faculty of Information and Communication Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File39.89 kBAdobe PDFView/Open
02_certificate.pdf781.58 kBAdobe PDFView/Open
03_abstract.pdf11.06 kBAdobe PDFView/Open
04_acknowledgement.pdf6.4 kBAdobe PDFView/Open
05_content.pdf29.3 kBAdobe PDFView/Open
06_chapter1.pdf13.71 kBAdobe PDFView/Open
07_chapter2.pdf593.53 kBAdobe PDFView/Open
08_chapter3.pdf107.76 kBAdobe PDFView/Open
09_chapter4.pdf418.13 kBAdobe PDFView/Open
10_chapter5.pdf628.17 kBAdobe PDFView/Open
11_chapter6.pdf757.36 kBAdobe PDFView/Open
12_chapter7.pdf710.94 kBAdobe PDFView/Open
13_chapter8.pdf10.76 kBAdobe PDFView/Open
14_reference.pdf32.66 kBAdobe PDFView/Open
15_publication.pdf5.99 kBAdobe PDFView/Open
16_vitae.pdf5.46 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: