Recognition using robust bit extraction
We present a novel technique for extracting bits from the perceptually significant components of an image transformation, thus making the recognition of objects under nonideal conditions robust. Specifically, we describe five popular face recognition transform methods [ including principal component...
| Main Authors: | , , |
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| Format: | Article |
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2005
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| Online Access: | http://shdl.mmu.edu.my/2183/ |
| _version_ | 1848789986779856896 |
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| author | Ngo, David C. L. Goh, Alwyn Teoh, Andrew B. J. |
| author_facet | Ngo, David C. L. Goh, Alwyn Teoh, Andrew B. J. |
| author_sort | Ngo, David C. L. |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | We present a novel technique for extracting bits from the perceptually significant components of an image transformation, thus making the recognition of objects under nonideal conditions robust. Specifically, we describe five popular face recognition transform methods [ including principal component analysis ( PCA), linear discriminant analysis ( LDA), wavelet transform, wavelet transform with PCA, and wavelet transform with Fourier-Mellin transform] with robust bit extraction enhancement for various numbers of bits extracted. The robustness guarantees that all similar face images will produce almost the same bits. This property is useful for generating cryptographic keys. The theoretical results are evaluated on the Olivetti Research Laboratory ( ORL) face database, showing that the extended methods significantly outperform the corresponding standard methods when the number of extracted bits reaches 100. (c) 2005 SPIE and IS&T. |
| first_indexed | 2025-11-14T18:05:26Z |
| format | Article |
| id | mmu-2183 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:05:26Z |
| publishDate | 2005 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-21832011-09-12T05:50:31Z http://shdl.mmu.edu.my/2183/ Recognition using robust bit extraction Ngo, David C. L. Goh, Alwyn Teoh, Andrew B. J. TA Engineering (General). Civil engineering (General) We present a novel technique for extracting bits from the perceptually significant components of an image transformation, thus making the recognition of objects under nonideal conditions robust. Specifically, we describe five popular face recognition transform methods [ including principal component analysis ( PCA), linear discriminant analysis ( LDA), wavelet transform, wavelet transform with PCA, and wavelet transform with Fourier-Mellin transform] with robust bit extraction enhancement for various numbers of bits extracted. The robustness guarantees that all similar face images will produce almost the same bits. This property is useful for generating cryptographic keys. The theoretical results are evaluated on the Olivetti Research Laboratory ( ORL) face database, showing that the extended methods significantly outperform the corresponding standard methods when the number of extracted bits reaches 100. (c) 2005 SPIE and IS&T. 2005-10 Article NonPeerReviewed Ngo, David C. L. and Goh, Alwyn and Teoh, Andrew B. J. (2005) Recognition using robust bit extraction. Journal of Electronic Imaging, 14 (4). 043016. ISSN 10179909 http://dx.doi.org/10.1117/1.2135321 doi:10.1117/1.2135321 doi:10.1117/1.2135321 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Ngo, David C. L. Goh, Alwyn Teoh, Andrew B. J. Recognition using robust bit extraction |
| title | Recognition using robust bit extraction |
| title_full | Recognition using robust bit extraction |
| title_fullStr | Recognition using robust bit extraction |
| title_full_unstemmed | Recognition using robust bit extraction |
| title_short | Recognition using robust bit extraction |
| title_sort | recognition using robust bit extraction |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://shdl.mmu.edu.my/2183/ http://shdl.mmu.edu.my/2183/ http://shdl.mmu.edu.my/2183/ |