IRIS Recognition System Using ICA, PCA, Daugman’s Rubber Sheet Model Together

It is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. However, limited by the real conditions, there are no very large common iris databases now. In this paper, an iris image synthesis method based on Principal Component Analysis (PCA), Independent component analysis (ICA) and Daugman’s rubber sheet model is proposed. Iris Recognition is a rapidly expanding method of biometric authentication that uses pattern-recognition techniques on images of iris to uniquely identify an individual. Algorithms have proven to be increasingly accurate and reliable after over 200 billion comparisons. The aim of this group project is to implement a working prototype of the techniques and methods used for iris recognition. Here we are comparing results of all three algorithms and showing the best technique used for iris recognition. As we are using three different algorithm the efficiency of project increases.