Open AccessFace recognition under illumination variations based on eight local directional patterns
Author(s) -
Faraji Mohammad Reza,
Qi Xiaojun
Publication year - 2015
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
eISSN - 2047-4946
pISSN - 2047-4938
DOI - 10.1049/iet-bmt.2014.0033
Subject(s) - computer science , artificial intelligence , computer vision , face (sociological concept) , facial recognition system , pixel , pattern recognition (psychology) , invariant (physics) , code (set theory) , mathematics , social science , sociology , set (abstract data type) , mathematical physics , programming language
Face recognition under varying illumination is a challenging task. This study proposes a modified version of local directional patterns (LDP), eight local directional patterns (ELDP), to produce an illumination insensitive representation of an input face image. The proposed ELDP code scheme uses Kirsch compass masks to compute the edge responses of a pixel's neighbourhood. Then, ELDP uses all the directional numbers to produce an illumination invariant image. The authors' extensive experiments show that the ELDP technique achieves an average recognition accuracy of 98.29% on the CMU‐PIE face database and 100% on the Yale B face database, and clearly outperforms the state‐of‐the‐art representative techniques.