Abstract
Local binary pattern (LBP), fast and simple for implementation, has shown its superiority in face and palmprint recognition. To extract representative features, "uniform" LBP was proposed and its effectiveness has been validated. However, all "non-uniform" patterns are clustered into one pattern, so a lot of useful information is lost. In this study, the authors propose to build a hierarchical multiscale LBP histogram for an image. The useful information of "non-uniform" patterns at large scale is dug out from its counterpart of small scale. The main advantage of the proposed scheme is that it can fully utilize LBP information while it does not need any training step, which may be sensitive to training samples. Experiments on one public face database and one palmprint database show the effectiveness of the proposed method.
Original language | English |
---|---|
Title of host publication | 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings |
Pages | 4521-4524 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 1 Dec 2010 |
Event | 2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong Duration: 26 Sept 2010 → 29 Sept 2010 |
Conference
Conference | 2010 17th IEEE International Conference on Image Processing, ICIP 2010 |
---|---|
Country/Territory | Hong Kong |
City | Hong Kong |
Period | 26/09/10 → 29/09/10 |
Keywords
- Face recognition
- LBP
- Multiscale
- Palmprint recognition
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Signal Processing