Abstract
This paper proposes an efficient indexing scheme that can be used for retrieval from a large iris database. For a given color iris query image, the proposed indexing scheme makes use of iris color to determine an index and uses this index to reduce the search space in the large iris database. Further, for query q, the retrieval technique uses iris texture to find the top best match from the reduced search space. The proposed technique has been tested on two publicly available color iris databases, viz UPOL [10] of 384 images and UBIRIS [13] of 1860 fully noisy images and is found to be robust against change in gaze, illumination, partial occlusions and scale. In both the databases, the test reveals that a small subspace is sufficient to achieve 100% hitrate for the top best match under various scales, illumination and partial occlusion. The performance of the proposed indexing scheme is analyzed against the group based color indexing scheme proposed in [14]. The results show that proposed indexing scheme is performing better as compared to group based color indexing scheme with respect to hitrate, penetration rate and CMC curve.
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