Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Iris Recognition with Low Template Size
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
A New Iris Recognition Method Using Independent Component Analysis
IEICE - Transactions on Information and Systems
Biometric scores fusion based on total error rate minimization
Pattern Recognition
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
Handbook of Multibiometrics
Iris recognition using LVQ neural network
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
IEEE Transactions on Circuits and Systems for Video Technology
A review of information fusion techniques employed in iris recognition systems
International Journal of Advanced Intelligence Paradigms
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This work presents a new method for feature extraction of iris images to improve the identification process. The valuable information of the iris is intrinsically located in its natural texture, and preserving and extracting the most relevant features is of paramount importance. The technique consists in several steps from adquisition up to the person identification. Our contribution consists in a multimodal algorithm where a fragmentation of the normalized iris image is performed and, afterwards, regional statistical descriptors with Self-Organizing-Maps are extracted. By means of a biometric fusion of the resulting descriptors, the features of the iris are compared and classified. The results with the iris data set obtained from the Bath University repository show an excellent accuracy reaching up to 99.867%.