(2D)2 FLD: An efficient approach for appearance based object recognition

Abstract

In this paper, a new technique called 2-directional 2-dimensional Fisher's Linear Discriminant analysis ((2D)² FLD) is proposed for object/face image representation and recognition. We first argue that the standard 2D-FLD method works in the row direction of images and subsequently we propose an alternate 2D-FLD which works in the column direction of images. To straighten out the problem of massive memory requirements of the 2D-FLD method and as well the alternate 2D-FLD method, we introduce (2D)² FLD method. The introduced (2D)² FLD method has the advantage of higher recognition rate, lesser memory requirements and better computing performance than the standard PCA/2D-PCA/2D-FLD method, and the same has been revealed through extensive experimentations conducted on COIL-20 dataset and AT&T face dataset.