An efficient color and texture based iris image retrieval technique

Abstract

This paper proposes a hierarchical approach to retrieve an iris image efficiently from for a large iris database. This approach is a combination of both iris color and texture. Iris color is used for indexing and texture is used for retrieval of iris images from the indexed iris database. An index which is determined from the iris color is used to filter out the images that are not similar to the query image in color. Further, iris texture features of those filtered images, are used to determine the images which are similar to the query image. The iris color information helps to design an efficient indexing scheme based on color indices. The color indices are computed by averaging the intensity values of all red and blue color pixels. Kd-tree is used for real-time indexing based on color indices. The iris texture features are obtained through Speeded Up Robust Features (SURF) algorithm. These features are used to get the query’s corresponding image at the top best match. The performance of the proposed indexing scheme is compared with two well known iris indexing schemes ( Mehrotra, Majhi, & Gupta, 2010; Puhan & Sudha, 2008) on UPOL ( Dobeš, Machala, Tichavský, & Pospı´šil, 2004) and UBIRIS ( Proencca & Alexandre, 2005) iris databases. It is observed that combination of iris color and texture improves the performance of iris recognition system.