Illumination pre‐processing method for face recognition using 2D DWT and CLAHE

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.