GABOR FILTER-BASED FACE RECOGNITION TECHNIQUE

Abstract

We propose a novel human face recognition approach in this paper, based on two-dimensional Gabor filtering and supervised classification. The feature extraction technique proposed in this article uses 2D Gabor filter banks and produces robust 3D face feature vectors. A supervised classifier, using minimum average distances, is developed for these vectors. The recognition process is completed by a threshold-based face verification method, also provided. A high facial recognition rate is obtained using our technique. Some experiments, whose satisfactory results prove the effectiveness of this recognition approach, are also described in the paper.