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A key concern with iris recognition systems is the time required to reliably find a test sample's match in a large database of subjects. This work considers methods for categorizing irises within a database, so that a search for a match to a test sample can be focused on the test sample's category. This work uses texton learning to reduce the representation of the images and then clusters the images...
Iris is a reliable biometric that is unique, remarkably stable through the life of an individual, and easy to capture. Many applications include verifying the identity of a subject or identifying an unknown individual from a list of possibilities that involve searching a large database. Prediction of ethnicity separates the data into subcategories that will make this search much faster. We have proposed...
The goal of this chapter is to give fundamental knowledge on solving multi-objective optimization problems. The focus is on the intelligent metaheuristic approaches (evolutionary algorithms or swarm-based techniques). The focus is on techniques for efficient generation of the Pareto frontier. A general formulation of MO optimization is given in this chapter, the Pareto optimality concepts introduced,...
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