Abstract: A method processes segmented iris images obtained by a non-cooperative image acquisition system to generate descriptors for features in the segmented iris image that are tolerant of segmentation error. The method includes receiving a segmented iris image, and selecting feature points in the segmented iris image to describe an iris locally.

Abstract: A method of generating a biometric feature descriptor has been developed that includes acquiring an image of an anatomical feature having a biometric feature, isolating a region of the image having the biometric feature, extracting image data from the image of the region to identify a plurality of features for the biometric feature, transforming the extracted image data for each identified feature into a plurality of feature descriptors, mapping the feature descriptors for the plurality of features into a first arrangement of feature descriptors, generating a second arrangement of feature descriptors with a non-invertible transform of the first arrangement of feature descriptors, and storing the second arrangement of feature descriptors into an electronic database.

Abstract: A method segments iris images from eye image data captured from non-cooperative subjects. The method includes receiving a frame of eye image data, and determining whether a pupil exists in the image by detecting glare areas in the image. Upon finding a pupil, subsequent images are processed with reference to the pupil location and a radius is calculated for the pupil. A k means clustering method and principal component analysis are used to locate pupil boundary points, which are fitted to a conic. Using the pupil boundary, an angular derivative is computed for each frame having a pupil and iris boundary points are fitted to a conic to identify an iris region between the iris boundary and the pupil boundary. Noise data are then removed from the iris region to generate an iris segment. A method for evaluating iris frame quality and iris image segmentation quality is also disclosed.

Abstract: An image quality measuring method enables a biometric image to be evaluated to determine whether the biometric image data are adequate for identification processing. The method includes converting a biometric image to dimensionless image data, filtering the dimensionless image data with a band pass filter, identifying a plurality of portions in the filtered data as containing identification features, each portion in the plurality having an information measurement that indicates feature content greater than portions in the filtered data that are excluded from the plurality, and measuring clarity for the biometric image from the identified plurality of portions in the filtered data.

Abstract: An iris recognition system and method generates a one-dimensional iris signature that is translation, rotation, illumination and scale invariant. It allows users to enroll poor quality iris images that would be rejected by conventional methods. In addition, the system and method generates a list of possible matches instead of only the best match. In this way, the users could potentially identify the iris image by deeper analysis (such as using traditional iris recognition algorithm for more accurate iris identification). Further, the system and method permits more toleration of noise (such as glare introduced by contact lens or eye glasses). Finally, the system and method improves iris identification process computational efficiency. The system stores a one-dimensional signature as opposed to the conventional two-dimensional image.