Face recognition under illumination variations based on eight local directional patterns

Mohammad Reza Faraji; Xiaojun Qi

Face recognition under illumination variations based on eight local directional patterns

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Author(s): Mohammad Reza Faraji ¹ and Xiaojun Qi ¹
- Affiliations: 1: Department of Computer Science, Utah State University, Logan, UT 84322-4205, USA
Source: Volume 4, Issue 1, March 2015, p. 10 – 17
DOI: 10.1049/iet-bmt.2014.0033 , Print ISSN 2047-4938, Online ISSN 2047-4946

Received 29/05/2014, Accepted 23/09/2014, Revised 29/08/2014, Published 19/01/2015

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.

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Face recognition under illumination variations based on eight local directional patterns

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