Iris Recognition System with Frequency Domain Features optimized with PCA and SVM Classifier

Applications such as immigration control, aviation security, bank and other financial transactions, access to defence organization requires a more reliable and authentic identification system. Iris is now considered to be one of the most time invariable biometric features of a person for recognition. Several iris recognition techniques were proposed with considerable focus on improving the false acceptance rate and minimizing false rejection rate. Most of the proposed techniques are tested with Mat lab and not keeping the detection and recognition time in mind. In this work we propose a novel iris recognition system with iris localization to segment and recognize color iris with highest speed and accuracy. Custom software for iris image processing is developed in C#.Net (.Net 3.5). Frequency domain magnitude and phase features are used for image feature representation. Support vector machines with “winner takes it all” configuration are used for classification. Tests shows 97% accuracy with average time of 31 milliseconds seconds for classifying each test image.