Published in

2010 IEEE International Conference on Image Processing

DOI: 10.1109/icip.2010.5653119

Links

Tools

Export citation

Search in Google Scholar

Hierarchical multiscale LBP for face and palmprint recognition

Proceedings article published in 2010 by Zhenhua Guo, Lei Zhang ORCID, David Zhang, Xuanqin Mou
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

2010 17th IEEE International Conference on Image Processing, ICIP 2010, Hong Kong, 26-29 September 2010 ; 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. ; Department of Computing ; Refereed conference paper