Multimodal Algorithm for Iris Recognition with Local Topological Descriptors

  • Sergio Campos
  • Rodrigo Salas
  • Hector Allende
  • Carlos Castro
Conference paper

DOI: 10.1007/978-3-642-10268-4_90

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)
Cite this paper as:
Campos S., Salas R., Allende H., Castro C. (2009) Multimodal Algorithm for Iris Recognition with Local Topological Descriptors. In: Bayro-Corrochano E., Eklundh JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer, Berlin, Heidelberg

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 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sergio Campos
    • 1
  • Rodrigo Salas
    • 2
  • Hector Allende
    • 1
  • Carlos Castro
    • 1
  1. 1.Dept. de InformáticaUniversidad Técnica Federico Santa MaríaValparaísoChile
  2. 2.Departamento de Ingeniería BiomédicaUniversidad de ValparaísoValparaísoChile

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