Name
Abstract | ||
|---|---|---|
To eliminate the effects of illumination variation, the conventional approaches firstly produce a compensation-based face image under standard illumination from the input image and then match the image with the face templates in a database. This method is not inapplicable to the input image with large illumination variation. Therefore, a novel method for varying illumination conditions is proposed. Firstly, the quotient image method is improved. Then, the nine basis images of each subject are generated by the improved quotient image method. Thirdly, one new image of each subject under the same lighting conditions with an input image is synthesized by the corresponding basis images. Finally, the synthetic images and the input image are projected to PCA plane to fulfill the recognition task. The experimental results show that the proposed approach can eliminate the effects of illumination variation and have a high recognition rate in the illumination conditions with remarkable changes. © 2012 Springer-Verlag London Limited. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s00521-012-1042-y | Neural Computing and Applications |
Keywords | Field | DocType |
Quotient image, Linear illumination subspace, Basis image, Face recognition | Facial recognition system,Computer vision,Pattern recognition,Quotient,Image processing,Artificial intelligence,Template,Image restoration,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
23 | 1 | 1433-3058 |
Citations | PageRank | References |
6 | 0.43 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhonghua Liu | 1 | 115 | 11.12 |
| Haixia Zhao | 2 | 126 | 13.44 |
| Jiexin Pu | 3 | 92 | 19.85 |
| Hui Wang | 4 | 177 | 43.68 |