Analysis of NIR and VW Light Iris Images on the Bases of Different Statistical Parameters

To carry out accurate research for person’s identification, it is necessary to know about NIR and VW images, by some easy method especially for iris recognition. This work presents method to know diversity and noise in the NIR and VW iris images, on the bases of eight different statistical parameters. For this work four VW databases: UBIRIS.v2, UBIRIS.v1 (season1), UBIRIS.v1 (season2), UPOL and four NIR databases: IIT Delhi.v1, CASIA.v1, CASIA.v4-iris interval, and CASIA.v4-iris twin were chosen. In calculated points, it is found that VW iris databases UBIRIS.v2 and UBIRIS.v1 (season2) posses most diversity. VW images are noisy compared to NIR images. Out of which UPOL images is most noisy. Intensity of VW images are less as compared to the NIR images. Average standard deviation of both NIR and VW images is equal (approx. 13.5).