Iris identification method based on local and global features
融合局部与全局特征提取的虹膜识别方法

Traditional iris recognition systems convert iris images into polar coordinates, and then normalized the images to achieve rotation invariance by rotating the feature vector. In order to decrease the complexity of typical iris recognition method, this paper presented a method of iris image identification based on global and local features that extracted from preprocessed iris image without normalizing. Firstly, it applied a bank of non-tensor product wavelet filters to extract the global features of iris. Secondly, it used a SIFT method to extract the local features of the selected regions. Finally, it tested the similarity distances of local and global features with different weights. Experimental results show that the proposed method has the correct recognition rate of 99. 065% when the equal error rate is 0. 935%. Without normalizing the iris images, the proposed approach can obtain very good recognition performance.