WCTFR : Wrapping Curvelet Transform Based Face Recognition

Abstract

The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Wrapping Curvelet Transform based Face Recognition (WCTFR). The Wrapping Curvelet Transform (WCT) is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT features of each image. The test image WCT features are compared with database images using Euclidean Distance (ED) to compute Equal Error Rate (EER) and True Success Rate (TSR). The proposed algorithm with WCT performs better than CurveletTransform algorithms used in [1], [10] and [11].

An improved iris recognition system based on the fusion of the curvelet and DTCWT

“…Generally, iris recognition system includes 5 steps like image acquisition, iris segmentation, iris normalization, feature encoding and feature matching [4], [12], [15], [19], [21], [22].…”