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영문 논문지

홈 홈 > 연구문헌 > 영문 논문지 > TIIS (한국인터넷정보학회)

TIIS (한국인터넷정보학회)

Current Result Document : 1,069 / 1,070

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  
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