A novel illumination normalization method based on local relation map
This paper presents a novel illumination normalization method to address the issue of illumination invariant face recognition. The proposed method applies a Difference of Gaussians (DoG) filter in the logarithm domain of the images to reduce the effects caused by the shadows. After that, a local rel...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/101917 http://hdl.handle.net/10220/12788 |
| _version_ | 1826128724447199232 |
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| author | Lian, Zhichao Er, Meng Joo Li, Juekun |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Lian, Zhichao Er, Meng Joo Li, Juekun |
| author_sort | Lian, Zhichao |
| collection | NTU |
| description | This paper presents a novel illumination normalization method to address the issue of illumination invariant face recognition. The proposed method applies a Difference of Gaussians (DoG) filter in the logarithm domain of the images to reduce the effects caused by the shadows. After that, a local relation map (LRM) is extracted as illumination invariant features for further recognition task. The proposed method outperforms the existing normalization approaches significantly based on the experimental results in the Yale B and Extended Yale B database. Moreover, the proposed method does not involve any prior information or modeling step and takes a low computational loan. Therefore it can be easily implemented in a real-time face recognition system. |
| first_indexed | 2024-10-01T07:29:17Z |
| format | Conference Paper |
| id | ntu-10356/101917 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:29:17Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1019172020-03-07T13:24:50Z A novel illumination normalization method based on local relation map Lian, Zhichao Er, Meng Joo Li, Juekun School of Electrical and Electronic Engineering IEEE Conference on Industrial Electronics and Applications (7th : 2012 : Singapore) DRNTU::Engineering::Electrical and electronic engineering This paper presents a novel illumination normalization method to address the issue of illumination invariant face recognition. The proposed method applies a Difference of Gaussians (DoG) filter in the logarithm domain of the images to reduce the effects caused by the shadows. After that, a local relation map (LRM) is extracted as illumination invariant features for further recognition task. The proposed method outperforms the existing normalization approaches significantly based on the experimental results in the Yale B and Extended Yale B database. Moreover, the proposed method does not involve any prior information or modeling step and takes a low computational loan. Therefore it can be easily implemented in a real-time face recognition system. 2013-08-01T04:32:04Z 2019-12-06T20:46:37Z 2013-08-01T04:32:04Z 2019-12-06T20:46:37Z 2011 2011 Conference Paper https://hdl.handle.net/10356/101917 http://hdl.handle.net/10220/12788 10.1109/ICIEA.2012.6360731 en |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Lian, Zhichao Er, Meng Joo Li, Juekun A novel illumination normalization method based on local relation map |
| title | A novel illumination normalization method based on local relation map |
| title_full | A novel illumination normalization method based on local relation map |
| title_fullStr | A novel illumination normalization method based on local relation map |
| title_full_unstemmed | A novel illumination normalization method based on local relation map |
| title_short | A novel illumination normalization method based on local relation map |
| title_sort | novel illumination normalization method based on local relation map |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/101917 http://hdl.handle.net/10220/12788 |
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