Showing papers by "Nalini K. Ratha published in 2009"

SLIC: Short-length iris codes

Abstract: The texture in a human iris has been shown to have good individual distinctiveness and thus is suitable for use in reliable identification. A conventional iris recognition system unwraps the iris image and generates a binary feature vector by quantizing the response of selected filters applied to the rows of this image. Typically there are 360 angular sectors, 64 radial rings, and 2 filter responses. This produces a full-length iris code (FLIC) of about 5760 bytes. In contrast, this paper seeks to shrink the representation by finding those regions of the iris that contain the most descriptive potential. We show through experiments that the regions close to the pupil and sclera contribute least to discrimination, and that there is a high correlation between adjacent radial rings. Using these observations we produce a short-length iris code (SLIC) of only 450 bytes. The SLIC is an order of magnitude smaller the FLIC and yet has comparable performance as shown by results on the MMU2 database. The smaller sized representation has the advantage of being easier to store as a barcode, and also reduces the matching time per pair.

An efficient, two-stage iris recognition system

Abstract: There have been claims of very high information content in iris texture, higher even than in fingerprints. This makes iris attractive for large scale identification systems with possibly millions of people. However, some systems operate by performing N 1:1 matches of the probe against the database. This can get prohibitively expensive in terms of computation as N grows large. Note that for identification systems the per-match time dominants system performance, unlike verification where feature extraction time is the primary component. In this paper we show how to use a short-length iris code to pre-screen a large database and thereby reduce the number of full comparisons needed to a fraction of the total. Since the screening code is much smaller than the full iris code, the time to process the whole database is greatly reduced. As an added benefit, we show that we can use the alignment inferred from the short code to greatly restrict the range of alignments searched for the full code, which further speeds up the system. As we demonstrate in experiments, the two stage approach can reduce the cost and/or time needed by an order of magnitude with very little impact on identification performance.

Fingerprint representation using gradient histograms

Abstract: Techniques for generating a gradient characterization for a first fingerprint image are provided. One or more fingerprint feature points are selected from the first fingerprint image. A region is obtained for each of the one or more selected fingerprint feature points. The region is a representation of an area proximate a given fingerprint feature point. Each of the obtained regions is divided into a plurality of sub-regions. A histogram is generated for each of the plurality of sub-regions. For each of the one or more selected fingerprint feature points, the one or more generated histograms are combined into a concatenated histogram. The concatenated histogram is used for identification purposes.

Iris recognition system and method

Abstract: A system and method for performing an identity search in a database of iris images for a probe iris image includes generating a full-length iris code and a compact iris code for iris images in a database, and generating a full-length iris code and a compact iris code for a probe iris image The compact iris code for the probe image is scored against all compact iris codes in the database A fraction of the database is retained based on score data The full length iris code for the probe image is scored against all the full length iris codes in the retained portion of the database