Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/2386
Title: Integrated approach for automated authentication based on biometrics and tools of image processing
Researcher: Devireddy, Srinivasa Kumar
Guide(s): Rao, T Venkateswara
MuraliKrishna, I V
Keywords: Biometrics, Fingerprint Matching, Multi biometrics
Upload Date: 25-Aug-2011
University: Jawaharlal Nehru Technological University
Completed Date: June, 2010
Abstract: Biometrics refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics. Although the problem of automatic fingerprint matching has been extensively studied, it is nevertheless, not a fully solved problem. In this thesis, an information fusion approach is adopted to address some of the limitations of existing fingerprint matching systems. A hybrid fingerprint system that utilizes both minutiae points and ridge feature maps to represent and match fingerprint images has been developed. The hybrid matcher is shown to perform significantly better than a traditional minutiae-based matcher. The ridge feature maps extracted by this technique have also been used to align and register fingerprint image pairs via a correlation process, thereby obviating the need to rely on minutiae points for image registration. To address the problem of partial prints obtained from smallsized sensors, a fingerprint mosaicking scheme has been developed. The proposed technique constructs a composite fingerprint template from two partial fingerprint impressions by using the iterative control point (ICP) algorithm that determines the transformation parameters relating the two impressions. To mitigate the effect of non-linear distortions in fingerprint images on the matching process, an average deformation model has been proposed. The model is developed by comparing a fingerprint impression with several other impressions of the same finger and observing the common ridge points that occur in them. An index of deformation has been suggested in this context to aid in the selection of an ‘optimal’ fingerprint impression from a set of impressions.
Pagination: xiii, 201p.
URI: http://hdl.handle.net/10603/2386
Appears in Departments:Faculty of Computer Science & Engineering

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01_title.pdfAttached File5.26 MBAdobe PDFView/Open
02_certificate.pdf215.75 kBAdobe PDFView/Open
03_acknowledgements.pdf219.12 kBAdobe PDFView/Open
04_abstract.pdf220.11 kBAdobe PDFView/Open
05_dedication.pdf112.98 kBAdobe PDFView/Open
06_table of contents.pdf641.98 kBAdobe PDFView/Open
07_list of tables.pdf534.16 kBAdobe PDFView/Open
08_list of figures.pdf654.54 kBAdobe PDFView/Open
09_chapter 1.pdf1.79 MBAdobe PDFView/Open
10_chapter 2.pdf1.12 MBAdobe PDFView/Open
11_chapter 3.pdf3.3 MBAdobe PDFView/Open
12_chapter 4.pdf1.95 MBAdobe PDFView/Open
13_chapter 5.pdf3.35 MBAdobe PDFView/Open
14_chapter 6.pdf1.88 MBAdobe PDFView/Open
15_chapter 7.pdf602.34 kBAdobe PDFView/Open
16_bibliography.pdf686.24 kBAdobe PDFView/Open


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