Iris image recognition based on independent component analysis and support vector machine

Abstract

The iris has a very unique texture and pattern, different for each individual and the pattern will remain stable, making possible what biometric technology call iris recognition. In this paper, 150 iris images from the Department of Computer Science, Palacky University in Olomouc iris database are used for iris recognition based on independent component analysis and support vector machine. There are three steps for developing this research namely, image preprocessing, feature extraction and recognition. The first step is image preprocessing in order to get the iris region from the eye image. The second is feature extraction by using independent component analysis in order to get the feature from the iris image. Support vector machine (SVM) is used for iris classification and recognition. In the end of this experiment, the implement method will be evaluated based upon Genuine Acceptance Rate (GAR). Experimental results show that the recognised rate from the variation of training data is 52% with one data train, 73% with two data trains and 90% three data trains. From the experimental result, it also shows that this technique produces a good performance.