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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| Format: | Thesis |
| Language: | English |
| Published: |
2009
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| Online Access: | http://hdl.handle.net/10356/18796 |
| _version_ | 1826110231349821440 |
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| author | Ravi Arvind Karmarkar |
| author2 | Ponnuthurai Nagaratnam Suganthan |
| author_facet | Ponnuthurai Nagaratnam Suganthan Ravi Arvind Karmarkar |
| author_sort | Ravi Arvind Karmarkar |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T02:31:01Z |
| format | Thesis |
| id | ntu-10356/18796 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:31:01Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | ntu-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 |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics Ravi Arvind Karmarkar Hierarchical palm-print recognition system for large databases |
| title | 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_short | Hierarchical palm-print recognition system for large databases |
| title_sort | hierarchical palm print recognition system for large databases |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics |
| url | http://hdl.handle.net/10356/18796 |
| work_keys_str_mv | AT raviarvindkarmarkar hierarchicalpalmprintrecognitionsystemforlargedatabases |