Title :
Face recognition under illumination variations based on eight local directional patterns
Author :
Faraji, Mohammad Reza ; Xiaojun Qi
Author_Institution :
Dept. of Comput. Sci., Utah State Univ., Logan, UT, USA
Abstract :
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.
Keywords :
edge detection; face recognition; image representation; lighting; CMU-PIE face database; ELDP code scheme; ELDP technique; Kirsch compass masks; Yale B face database; edge responses; eight LDP; face recognition; illumination insensitive representation; illumination invariant image; illumination variations; input face image; local directional patterns; pixel neighbourhood; recognition accuracy;
Journal_Title :
Biometrics, IET
DOI :
10.1049/iet-bmt.2014.0033