In recent years, automatically recognizing irisplays a vital role in real world applications. Iris recognition is the automated biometric recognition technique based on iris patterns obtained from human iris images. The unique pattern of iris makes iris recognition system more accurate. Many novel methods have been proposed to tackle the automatic Iris recognition problem. One of the difficult issues for a successful iris recognition system is, to design a robust system with fake detection features. In the proposed method, Fake detection features and textural features are used for the recognition of human iris. Input images are obtained from CASIA v4 database. Input image obtained are enhanced using histogram equalization. Features are obtained directly from the histogram equalized image and are stored in the database. In the matching phase, the features of test image is compared with already extracted features that are stored in the database. This is done by using Support Vector Machine (SVM) classifier. If both the feature of test image and feature that are stored in the database matches, the person will be authorized else the person will be unauthorized. This method produces high degree of accuracy.
Iris recognition, Histogram equalization, Textural features, Fake detection features, Support Vector Machine Classifier (SVM)
