Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/73895
Title: Hand Based Biometric Identification using Energy Compaction in Transform Domain including New Multi resolution Hybrid Wavelet
Researcher: Vig Rekha
Guide(s): Kekre H. B.
Keywords: Applications
Biometrics
Databases
Fingerprint
Hybrid Wavelets
Orthogonality
Palmprints
Transform
University: Narsee Monjee Institute of Management Studies
Completed Date: 
Abstract: The hand-based biometrics viz. fingerprint, palmprint, finger-knuckle print etc. are the most popular among all the biometrics currently in use. The main advantages of using hand-based biometrics are user acceptability, ease of acquisition and plenteous, stable features. Hand-based biometric identification systems have enormous and ever-increasing applications. From electronic banking to airport security and from forensics to user identification cards, these hand-based biometrics find applications in all arenas. A Hand-based biometric identification system recognizes an individual by matching the features of its biometric with the enrolled templates in the database. newlineIn this work, three hand-based biometrics viz. fingerprint, palmprint and finger-knuckle print have been used for identification. The biometric trait is supposed to be unique for each human being. This uniqueness needs to be extracted in the form of features and used for identification. Feature extraction is performed in both enrollment and identification phases. The features of each of the three hand-based biometrics have been extracted using four main approaches. All the four approaches are in transform domain and use the energy compaction property of transforms, which has been used in a unique way to extract the features. newline
Pagination: 
URI: http://hdl.handle.net/10603/73895
Appears in Departments:Department of Technology Management

Files in This Item:
File Description SizeFormat 
00. title page.pdfAttached File12.36 kBAdobe PDFView/Open
01. certificate.pdf8.07 kBAdobe PDFView/Open
02. declaration.pdf7.89 kBAdobe PDFView/Open
03. thesis approval certificate.pdf6.17 kBAdobe PDFView/Open
04. acknowledgements.pdf7.63 kBAdobe PDFView/Open
05. abstract.pdf22.24 kBAdobe PDFView/Open
06. organization of the thesis.pdf15.19 kBAdobe PDFView/Open
07. table of contents.pdf33.21 kBAdobe PDFView/Open
08. list of figures.pdf54.78 kBAdobe PDFView/Open
09. list of tables.pdf24.08 kBAdobe PDFView/Open
10. list of abbreviations.pdf12.56 kBAdobe PDFView/Open
11. chapter 1.pdf315.08 kBAdobe PDFView/Open
12. chapter 2.pdf495.39 kBAdobe PDFView/Open
13. chapter 3.pdf943.08 kBAdobe PDFView/Open
14. chapter 4.pdf402.22 kBAdobe PDFView/Open
15. chapter 5.pdf376.94 kBAdobe PDFView/Open
16. chapter 6.pdf368.11 kBAdobe PDFView/Open
17. chapter 7.pdf351.63 kBAdobe PDFView/Open
18. chapter 8.pdf192.85 kBAdobe PDFView/Open
19. chapter 9.pdf204.32 kBAdobe PDFView/Open
20. reference.pdf141.13 kBAdobe PDFView/Open


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