TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
RowAMD Distance: A Novel 2DPCA-Based Distance Computation with Texture-Based Technique for Face Recognition |
| 영문제목(English Title) |
RowAMD Distance: A Novel 2DPCA-Based Distance Computation with Texture-Based Technique for Face Recognition |
| 저자(Author) |
Waled Hussein Al-Arashi
Chai Wuh Shing
Shahrel Azmin Suandi
|
| 원문수록처(Citation) |
VOL 11 NO. 11 PP. 5474 ~ 5490 (2017. 11) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Although two-dimensional principal component analysis (2DPCA) has been shown to be successful in face recognition system, it is still very sensitive to illumination variations. To reduce the effect of these variations, texture-based techniques are used due to their robustness to these variations. In this paper, we explore several texture-based techniques and determine the most appropriate one to be used with 2DPCA-based techniques for face recognition. We also propose a new distance metric computation in 2DPCA called Row Assembled Matrix Distance (RowAMD). Experiments on Yale Face Database, Extended Yale Face Database B, AR Database and LFW Database reveal that the proposed RowAMD distance computation method outperforms other conventional distance metrics when Local Line Binary Pattern (LLBP) and Multi-scale Block Local Binary Pattern (MB-LBP) are used for face authentication and face identification, respectively. In addition to this, the results also demonstrate the robustness of the proposed RowAMD with several texture-based techniques.
|
| 키워드(Keyword) |
2DPCA
face recognition
Local Line Binary Pattern
Multiscale Block Local Binary Pattern
RowAMD
|
| 파일첨부 |
PDF 다운로드
|
