@inproceedings{c5bfd7aaeabc486b9b1e1e4de1f04e9e,
title = "Relaxed local ternary pattern for face recognition",
abstract = "Local binary pattern (LBP) is sensitive to noise. Local ternary pattern (LTP) partially solves this problem by encoding the small pixel difference into a third state. The small pixel difference may be easily overwhelmed by noise. Thus, it is difficult to precisely determine its sign and magnitude. In this paper, we propose the concept of uncertain state to encode the small pixel difference. We do not care its sign and magnitude, and encode it as both 0 and 1 with equal probability. The proposed Relaxed LTP is tested on the CMU-PIE database, the extended Yale B database and the O2FN mobile face database. Superior performance is demonstrated compared with LBP and LTP.",
keywords = "Face Recognition, Local Binary Pattern, Local Ternary Pattern, Relaxed LTP, Uncertain State",
author = "Jianfeng Ren and Xudong Jiang and Junsong Yuan",
note = "Copyright: Copyright 2014 Elsevier B.V., All rights reserved.; 2013 20th IEEE International Conference on Image Processing, ICIP 2013 ; Conference date: 15-09-2013 Through 18-09-2013",
year = "2013",
doi = "10.1109/ICIP.2013.6738759",
language = "English",
isbn = "9781479923410",
series = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
publisher = "IEEE Computer Society",
pages = "3680--3684",
booktitle = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
address = "United States",
}