Hierarchical palm-print recognition system for large databases

As palm-print recognition systems gain popularity in the market, there is a growing need to design efficient and accurate algorithms. There is a possibility especially in big organizations that large number of people will make use of the system. It is required that the system is robust enough to han...

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主要作者: Ravi Arvind Karmarkar
其他作者: Ponnuthurai Nagaratnam Suganthan
格式: Theses and Dissertations
語言:English
出版: 2009
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在線閱讀:http://hdl.handle.net/10356/18796
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機構: Nanyang Technological University
語言: English
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spelling sg-ntu-dr.10356-187962023-07-04T15:28:22Z Hierarchical palm-print recognition system for large databases Ravi Arvind Karmarkar Ponnuthurai Nagaratnam Suganthan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics As palm-print recognition systems gain popularity in the market, there is a growing need to design efficient and accurate algorithms. There is a possibility especially in big organizations that large number of people will make use of the system. It is required that the system is robust enough to handle such a large amount of data. The number of users could be of the order of several hundreds or even thousands. In this work, a 3 stage recognition process has been developed which ensures fast operation while maintaining a high level of accuracy and is capable of handling large databases. The two distinct levels of matching are coarse-level matching and fine-level matching. The first 2 stages are coarse level matching stages which make use of hand geometry and standard deviation values of the local intensity levels. The 3rd stage is a fine level matching stage which uses Gabor filtering to generate Palm-print Phase and Orientation Code (PPOC) and matches two feature sets using modified Hamming distance. The results obtained are very impressive and clearly show the advantage of using a 3-stage process. Master of Science (Computer Control and Automation) 2009-07-20T01:55:04Z 2009-07-20T01:55:04Z 2008 2008 Thesis http://hdl.handle.net/10356/18796 en 63 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics
Ravi Arvind Karmarkar
Hierarchical palm-print recognition system for large databases
description As palm-print recognition systems gain popularity in the market, there is a growing need to design efficient and accurate algorithms. There is a possibility especially in big organizations that large number of people will make use of the system. It is required that the system is robust enough to handle such a large amount of data. The number of users could be of the order of several hundreds or even thousands. In this work, a 3 stage recognition process has been developed which ensures fast operation while maintaining a high level of accuracy and is capable of handling large databases. The two distinct levels of matching are coarse-level matching and fine-level matching. The first 2 stages are coarse level matching stages which make use of hand geometry and standard deviation values of the local intensity levels. The 3rd stage is a fine level matching stage which uses Gabor filtering to generate Palm-print Phase and Orientation Code (PPOC) and matches two feature sets using modified Hamming distance. The results obtained are very impressive and clearly show the advantage of using a 3-stage process.
author2 Ponnuthurai Nagaratnam Suganthan
author_facet Ponnuthurai Nagaratnam Suganthan
Ravi Arvind Karmarkar
format Theses and Dissertations
author Ravi Arvind Karmarkar
author_sort Ravi Arvind Karmarkar
title Hierarchical palm-print recognition system for large databases
title_short Hierarchical palm-print recognition system for large databases
title_full Hierarchical palm-print recognition system for large databases
title_fullStr Hierarchical palm-print recognition system for large databases
title_full_unstemmed Hierarchical palm-print recognition system for large databases
title_sort hierarchical palm-print recognition system for large databases
publishDate 2009
url http://hdl.handle.net/10356/18796
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