The Effect of Iris Image Compression on Recognition Performance

In today's modern society automated personal identification based on biometrics has received attention not only from research community but also from industries for security applications. Iris recognition is emerging as one of the most active topics in biometrics technology because of its high reliability for identification of persons & is a proved to be most accurate means to identify persons. Iris is consider as the most reliable biometric feature in terms of its uniqueness and robustness. For Iris Recognition iris image (eye image )is captured from different person's and these iris images should be stored in the data base & recalled whenever required. So there is requirement of large databases of iris images. If available storage space is not enough for these images, compression will be an option. Compression allows a reduction in the space needed to store these iris images. The objective of this paper is to present the effects of iris image compression on the recognition performance. Normally, iris images are 600 times bigger than the Iris Code templates which required larger space for storage .But it is expected that iris data should be stored, transmitted, and embedded in media in the form of images rather than as templates. To obtain this goal with its implications for bandwidth and storage, this paper present the scheme that combine region-of-interest isolation with JPEG ,JPEG 2000 & lifting based wavelet compression at different levels using publicly available database of iris images. It is concluded that lifting wavelet compression gives the better result as compared to JPEG & JPEG 2000 with minimum impact on recognition performance.