Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition

A novel image classification algorithm named Adaptively Weighted Sub-directional Two-Dimensional Linear Discriminant Analysis (AWS2DLDA) is proposed in this paper. AWS2DLDA can extract the directional features of images in the frequency domain, and it is applied to face recognition. Some experiments are conducted to demonstrate the effectiveness of the proposed method. Experimental results confirm that the recognition rate of the proposed system is higher than the other popular algorithms.

Research highlights
► The directionality of images is introduced to face recognition.
► The discriminant power in each direction of images is computed.
► Features with information of directionality have more discriminant power.