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Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Volume 5856 of the series Lecture Notes in Computer Science pp 766-773

Multimodal Algorithm for Iris Recognition with Local Topological Descriptors

  • Sergio CamposAffiliated withDept. de Informática, Universidad Técnica Federico Santa María
  • , Rodrigo SalasAffiliated withDepartamento de Ingeniería Biomédica, Universidad de Valparaíso
  • , Hector AllendeAffiliated withDept. de Informática, Universidad Técnica Federico Santa María
  • , Carlos CastroAffiliated withDept. de Informática, Universidad Técnica Federico Santa María

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Abstract

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%.

Keywords

Iris recognition SOM Voronoi polygons regions descriptors