An Improvement of Iris Pattern Identification Using Radon Transform

This research proposes an improvement of iris personal identification system using Radon transform which is used to extract feature stored as templates in a database. In Personal identification using iris images, the computational complexity in the feature extraction from the normalized iris images is still of key concern and further efforts are required to develop efficient feature extraction approaches. In this paper, we investigate a new approach for the efficient and effective extraction of iris features using Radon transforms. In our research, Euclidean distance is used for distance measurement.