Please use this identifier to cite or link to this item:
Title: Enhancing local binary patterns distinctiveness for face representation
Authors: Ghahramani, Mohammad
Yau, Wei-Yun
Teoh, Eam Khwang
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2011
Source: Ghahramani, M., Yau, W. Y., & Teoh, E. K. (2011). Enhancing local binary patterns distinctiveness for face representation. IEEE International Symposium on Multimedia (ISM), 440-445.
Abstract: The Local Binary pattern (LBP) is a well-known feature and has been widely used for human identification. However, the amount of information extracted is limited which reduces the LBP discriminative power. Recently, some enhancements have been proposed by adding preprocessing stages or considering more neighbor pixels to enrich the extracted feature. In this paper, we propose Uniformly-sampled Thresholds for LBP (UTLBP) operator that increases the richness of information derived from the LBP feature. It outperforms other features in various probe sets of the large CAS-PEAL database for face recognition. Moreover, we collected a database of 25 families to verify the superiority of the proposed feature in the family verification. Results show that using the UTLBP, the total error in face recognition and family verification is reduced up to 8% and 3% respectively comparing to the state of the art LBP. It improves the missing family member verification performance up to 3% where, contrary to expectation, increasing the LBP operator radius worsens the performance by 2%.
DOI: 10.1109/ISM.2011.78
Rights: © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

Files in This Item:
File Description SizeFormat 
Enhancing Local Binary Patterns Distinctiveness for Face Representation.pdf305.32 kBAdobe PDFThumbnail

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.