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An Improved Illumination Normalization and Robust Feature Extraction Technique for Face Recognition Under Varying Illuminations

  • Jyotsna YadavEmail author
  • Navin rajpal
  • Rajesh Mehta
Research Article - Computer Engineering and Computer Science

Abstract

Invariant feature extraction under diverse illuminations is challenging for face recognition. Light intensity variations in face images are predominant in large-scale features. In existing techniques, such features are truncated to achieve illumination-invariant features. However, salient features are lost during small-scale feature extraction that affect performance. Thus, objective in proposed work is to attain improved illumination normalization where large-scale and small-scale feature information is efficiently extracted for face recognition. First, reflectance ratio and histogram equalization (RRHE)-based new illumination normalization framework is proposed in which illumination deviations are annulled. Then, histogram equalization is employed to enhance contrast of reflectance ratio image by adjusting pixel intensities. Then, robust feature extraction in discrete wavelet packet transform domain (RFDWPT) from RRHE images is performed using various orthogonal wavelets with distinct vanishing moments. Here, small-scale features (noise effect) of RRHE images are discarded and final feature vector is formed by appropriate small-scale and large-scale features. This results in illumination-normalized salient features for eigen space analysis where nearest neighbor classification is performed on compact size training and test features. Compared with other face recognition techniques under different illumination conditions, significant enhancement in recognition accuracy is achieved on benchmark databases such as Yale B, CMU-PIE, Yale and extended Yale B.

Keywords

Discrete wavelet packet transform Face recognition Illumination normalization Reflectance ratio Robust feature extraction 

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Copyright information

© King Fahd University of Petroleum & Minerals 2019

Authors and Affiliations

  1. 1.University School of Information and Communication TechnologyGuru Gobind Singh Indraprastha UniversityDwarkaIndia
  2. 2.Computer Science and Engineering DepartmentThapar Institute of Engineering and TechnologyPatialaIndia

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