An Iris Texture Feature Based Radial Basis Neural Network Classifier with Enhanced Performance. (2016)

• Record Type: Journal Article
• Authors: Devi, P.S. Aparna; Mini, M.G.
• Is Part Of: Procedia technology. Volume 24(2016)
• Page Start: 996
• Page End: 1001
• Publication Date: 2016
• Subjects: Iris -- statistical texture features -- Radial Basis neural network classifier -- Distinction Parameter; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.05.218
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: Iris detection and classification has been a problem of real significance in the fields of image processing and medical electronics. In this paper, an efficient texture based statistical feature extraction and classification based on a novel Distinction Parameter has been proposed. The proposed technique makes use of standard iris image databases and efficient radial basis neural network architecture for classification. Various simulation results have also been presented in this paper