DOI:10.20894/IJDMTA.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.893 & GIF:0.787
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded
Facial recognition systems are biometric methods used to pinpoint the identities of faces present in various digital formats by comparing them to facial databases. The variation in illuminating conditions is a huge hindrance for efficient operation of facial verification systems. The effects of change in ambient lighting conditions and formation of shadows can be nullified by an effortless pre-processing system. This paper presents an effectual Facial Recognition System which consists of three stages: the illumination insensitive preprocessing method, Feature Extraction and Score Fusion. In the preprocessing stage, the light-sensitive images are converted to light-insensitive images so that uncontrolled lighting will no more be a liability for any kind of identification. In the feature extraction stage, hybrid Fourier classifiers are used to obtain transforms which are projected into subspaces using PCLDA Theory. And the output is passed onto the Score Fusion stage where the discriminating powers of the classifiers are unified by using LLR and knowing the ground truth optimizations. This proposal has passed the Face Recognition Grand Challenge (FRGC) Version-2 Experiment, Extended Yale B and FERET datasets.
