Adaptive gamma correction-based expert system for nonuniform illumination face enhancement

Abdelhamid Iratni; Mustapha Aouache; Oulefki Adel

doi:10.1117/1.JEI.27.2.023028

23 April 2018 Adaptive gamma correction-based expert system for nonuniform illumination face enhancement

Abdelhamid Iratni, Mustapha Aouache, Oulefki Adel

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 2, 023028 (April 2018). https://doi.org/10.1117/1.JEI.27.2.023028

Abstract

The image quality of a face recognition system suffers under severe lighting conditions. Thus, this study aims to develop an approach for nonuniform illumination adjustment based on an adaptive gamma correction (AdaptGC) filter that can solve the aforementioned issue. An approach for adaptive gain factor prediction was developed via neural network model-based cross-validation (NN-CV). To achieve this objective, a gamma correction function and its effects on the face image quality with different gain values were examined first. Second, an orientation histogram (OH) algorithm was assessed as a face’s feature descriptor. Subsequently, a density histogram module was developed for face label generation. During the NN-CV construction, the model was assessed to recognize the OH descriptor and predict the face label. The performance of the NN-CV model was evaluated by examining the statistical measures of root mean square error and coefficient of efficiency. Third, to evaluate the AdaptGC enhancement approach, an image quality metric was adopted using enhancement by entropy, contrast per pixel, second-derivative-like measure of enhancement, and sharpness, then supported by visual inspection. The experiment results were examined using five face’s databases, namely, extended Yale-B, Carnegie Mellon University-Pose, Illumination, and Expression, Mobio, FERET, and Oulu-CASIA-NIR-VIS. The final results prove that AdaptGC filter implementation compared with state-of-the-art methods is the best choice in terms of contrast and nonuniform illumination adjustment. In summary, the benefits attained prove that AdaptGC is driven by a profitable enhancement rate, which provides satisfying features for high rate face recognition systems.

Citation Download Citation

Abdelhamid Iratni, Mustapha Aouache, and Oulefki Adel "Adaptive gamma correction-based expert system for nonuniform illumination face enhancement," Journal of Electronic Imaging 27(2), 023028 (23 April 2018). https://doi.org/10.1117/1.JEI.27.2.023028

Received: 19 October 2017; Accepted: 29 March 2018; Published: 23 April 2018

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available