access icon free Illumination pre-processing method for face recognition using 2D DWT and CLAHE

© The Institution of Engineering and Technology
Received 08/06/2016, Accepted 26/09/2017, Revised 18/02/2017, Published 03/10/2017

This study presents an illumination pre-processing method termed as ‘Discrete wavelet transform enhanced contrast limited adaptive histogram equalisation’ (DWT E-CLAHE) to recognise the front view facial images in the difficult light conditions. A recent image enhancement method CLAHE-DWT motivates to combine the two-dimensional discrete wavelet transform (2D DWT) and CLAHE. The DWT E-CLAHE is implemented as follows: The original image is enhanced using the Gamma intensity correction (GIC); then split into low-frequency and high-frequency components using 2D DWT; finally, to the low-frequency components, the logarithmic transform, GIC and CLAHE are applied in the sequential order. The face recognition of DWT E-CLAHE is made using Gabor magnitude features. The face recognition of CLAHE-DWT is implemented for the first time. The experimental results of DWT E-CLAHE in the various face databases prove the following: (i) The proper selection of parameters of DWT E-CLAHE improves the brightness and contrast of the image. (ii) The recognition accuracy of DWT E-CLAHE in the Carnegie Mellon University (CMU) Pose, Illumination, and Expression (PIE) and Extended Yale B databases are extremely good, since the brightness and contrast are improved significantly. (iii) The performance comparison of DWT E-CLAHE outperforms CLAHE-DWT and state-of-the-art face recognition methods. (iv) DWT E-CLAHE recognises the varying facial expressions.

Inspec keywords: image enhancement; face recognition; brightness; Gabor filters; discrete wavelet transforms; visual databases; emotion recognition

Other keywords: Gabor magnitude features; face recognition; Gamma intensity correction; light conditions; extended Yale B; GIC; front view facial images; contrast; discrete wavelet transform enhanced contrast limited adaptive histogram equalisation; two-dimensional discrete wavelet transform; 2D DWT; brightness; low-frequency components; CMU PIE; high-frequency components; illumination preprocessing method; image enhancement method CLAHE-DWT; facial expression recognition; logarithmic transform; face databases

Subjects: Spatial and pictorial databases; Integral transforms; Image recognition; Computer vision and image processing techniques; Filtering methods in signal processing; Integral transforms

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