Research Article Open Access

Recognition of Faces using Efficient Multiscale Local Binary Pattern and Kernel Discriminant Analysis in Varying Environment

Sujata G. Bhele1 and V.H. Mankar2
  • 1 Priyadarshini College of Engg, India
  • 2 Government Polytechnic, India

Abstract

Face recognition involves matching face images with different environmental conditions. Matching face images with different environmental conditions is not a easy task. Also matching face images considering variations such as changing illumination, pose, facial expression and that with uncontrolled conditions becomes more difficult. This paper focuses on accurately recognizing face images considering all the above variations. The proposed system is based on collecting features from face images using Multiscale Local Binary pattern (MLBP) with eight orientations out of 59 crucial ones and then finding similarity using a kernel linear discriminant analysis. Literature suggested that MLBP can give up to 256 orientations for a single radius considered around a pixel and its neighborhood. The paper uses only 8 orientations for a single radius and four such radii (1, 3, 5 and 7) are considered around a single pixel with (8x4) 32 histogram features thus reducing the computational complexity. Various face image databases are considered in this paper namely, Labeled Faces in Wild (LFW), Japanese Female Facial Expression (JAFFE), AR and Asian. Results showed that the proposed system correctly identified 9 out of 10 subjects. The proposed system involves preprocessing including alignment and noise reduction using a Gaussian filter, feature extraction using MLBP based histograms and matching based on kernel linear discriminant analysis.

American Journal of Engineering and Applied Sciences
Volume 10 No. 3, 2017, 726-732

DOI: https://doi.org/10.3844/ajeassp.2017.726.732

Submitted On: 19 June 2017 Published On: 31 August 2017

How to Cite: Bhele, S. G. & Mankar, V. (2017). Recognition of Faces using Efficient Multiscale Local Binary Pattern and Kernel Discriminant Analysis in Varying Environment. American Journal of Engineering and Applied Sciences, 10(3), 726-732. https://doi.org/10.3844/ajeassp.2017.726.732

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Keywords

  • Face Recognition
  • Uncontrolled Conditions
  • Local Binary Pattern (LBP)
  • Multi-Scale Local Binary Pattern (MLBP)
  • Histogram Features
  • Discriminant Analysis