2D2LPI

Abstract

In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy.