IRIS RECOGNITION USING MODULAR NEURAL NETWORK AND FUZZY INFERENCE SYSTEM BASED SCORE LEVEL FUSION

Abstract

Iris Recognition System (IRS) is one of the prominent recognition system used in various application domains such as border control, access control, airports and citizen registration to accurately identify a person. The IRS generally consists of four steps viz. Image Acquisition, Feature Extraction, Segmentation and Recognition. This paper proposes an approach for recognition of an iris using Modular Neural Network and Fuzzy Logic based Score Level Fusion. The performance of the proposed approach is tested on the standard iris database, IITD, obtained from the public domain digital repository. The experimental results demonstrate the efficiency of the proposed approach for identification and verification of an iris image with the considered dataset when considering different performance measures.