Comparison of Detection Accuracy and Effect of JPEG2000 Compression on Iris Recognition

In today's digital world, identification based on biometrics has received much attention from research community as well as from industries for security applications. Iris recognition is evolving as one of the most active techniques in biometrics technology accounting to its high reliability for identification and is proved to be most error free means to identify persons. Iris is considered as the reliable biometric feature based on its uniqueness and robustness. To perform iris recognition iris/eye image is captured from numerous person's and these images should be stored in the data base & retrieved whenever required. Hence there is need of huge databases of iris images. Compression is a unique option available if available storage space is not sufficient for the images. Compression empowers a reduction in the space needed to store these iris images. The aim of this paper is to present the effects of iris image compression on the recognition performance. Usually iris images are 600 times bigger than the Iris Code templates which requires enormous space for storage. It is expected that iris data should be secured, transmitted and embedded in media in the form of images instead of templates. To obtain this objective considering its implications for bandwidth and storage, this paper presents the scheme that combine ROI(region-of-interest) isolation with JPEG 2000 compression at different levels using publicly available database of iris images each in case of two cases of Normalized iris images on with classic Daughman's rubber sheet model and the second one through non-linear Biomechanical model. It is concluded that JPEG 2000 compression gives the better results with iris images normalized with Biomechanical model with minimum impact on recognition performance. General Terms Iris Recognition, Biometrics, Authentication systems et. al.