Iris recognition using 2D-LDA + 2D-PCA

Abstract

This paper presents a biometric iris recognition using 2D-LDA with embedding 2D-PCA. A new approach that the 2D-PCA is embedded into the 2D-LDA to improve its performance is proposed. The approach first finds the most concentrated training samples in each class, and uses the sample mean to represent the class. Then the 2D-PCA is adopted to find the projection matrix which can scatter the variance between classes. The results show that the new approach has an encouraging performance. The recognition rate up to 99.20% can be achieved.