Illumination Invariant Face Recognition Using Gabor Wavelet Function

Ranjith, Chukka (2018) Illumination Invariant Face Recognition Using Gabor Wavelet Function. MTech thesis.

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Abstract

Illumination variation changes the appearance of faces and makes it very difficult for accurate recognition. Face recognition in an uncontrolled environment is still a challenging task for the researcher. In this paper, we propose a Fourier transform (FT) based illumination normalization and Gabor wavelets based feature extraction for proper face representation for better classification. Implementing FT and Gabor wavelets in this method is to make the system more robust to the various constraints like illumination and noise where the performances of the other systems are degraded. Considering the phase magnitude information in the frequency domain, the illumination is compensated and using the Gabor filters noise and other unwanted disturbances like facial expressions are discarded. The extensive experimental results, on the publicly available Extended Yale-B face database, show that the proposed method performs better than the well known systems even if on the extremely poor illumination images.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Illumination normalization; Face recognition; Fourier transform; Gabor wavelet; Feature extraction
Subjects:Engineering and Technology > Electronics and Communication Engineering > Image Processing
Engineering and Technology > Electronics and Communication Engineering > Signal Processing
Divisions: Engineering and Technology > Department of Electronics and Communication Engineering
ID Code:9987
Deposited By:IR Staff BPCL
Deposited On:06 Jun 2019 15:45
Last Modified:06 Jun 2019 15:45
Supervisor(s):Meher, Sukadev

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