An Illumination Pre-processing Method Using the Enhanced Energy of Discrete Wavelet Transform for Face Recognition

ABSTRACT

Automatic face recognition is useful in a wide range of applications. The accuracy of a face recognition system is adversely affected due to illumination variations. This study presents an illumination pre-processing method, “Enhanced Energy Discrete Wavelet Transform”, to increase recognition accuracy of front view faces under varying illuminations. This method is implemented as follows. A two-dimensional Discrete Wavelet Transform (2D DWT) decomposes the original image into four frequency sub-bands, namely low-low, low-high, high-low and high-high. The energy of each sub-band is computed. A weighting scheme is employed to increase the energy. The weighting scheme computes weight of sub-band based on its energy and threshold. The new sub-bands are obtained by multiplying sub-band, weight and weighting factor. Then, the new four sub-bands are added to create enhanced energy DWT image. The face recognition is carried out using Gabor magnitude features. The experiments are conducted in facial images of Yale, Pose Illumination Expression (PIE) and Extended Yale B. The results proves that low-low sub-band has maximum weight. The performance analysis is carried out using different threshold and weighting factor values. The weighting factor increases energy of low-low sub-band. The analysis of energy enhancement shows increase in energy of 20.96% and 31.88% in CMU PIE and Extended Yale B, respectively. The increase of energy improves the brightness of image. The recognition accuracy in CMU PIE and Extended Yale B is 99.02% and 99.82%, respectively. The comparative analysis with the state-of-the-art methods proves that the proposed method is an effective illumination pre-processing method.

KEYWORDS:

• Discrete wavelet transform
• Enhanced energy
• Face recognition
• Illumination pre-processing

Additional information

Notes on contributors

A. Thamizharasi

A Thamizharasi is working as Associate Professor in the Department of Computer Science and Engineering, Mohandas College of Engineering and Technology, Trivandrum, Kerala, India. She obtained doctoral degree in computer science and engineering from Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu. She has 16 years of teaching experience. She has organized many workshops and conferences. Her PhD title is “Hybrid Illumination Pre-processing Methods for Face Recognition”. Her research interest are on image processing, machine learning and pattern recognition. She had published research papers in international journals and conferences.

Jayasudha J. S.

Jayasudha J S is working as Professor in the department of computer Science & Engineering, Sree Chitra Thirunal College of Engineering, Thiruvananthapuram. She has 21 years of teaching experience. She has organized many community development programmes, short-term courses and conferences. She did her BE degree from Madurai Kamaraj University and ME degree from National Institute of Technology, Trichy and doctorate degree from University of Kerala. Her PhD thesis title is “Web caching and Pre-fetching techniques for Web traffic/Latency reduction”. She is recognized as approved research guide in the PhD programme in Kerala University, Manonmaniam Sundaranar University and Noorul Islam University. She is also doing research in computer networks and image processing. She has published her research works in many national and international conferences and journals. Email: [email protected]