Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Iris Segmentation based on Fuzzy Mathematical Morphology, Neural Networks and Ontologies
Year:2009
Research Areas
  • Mathematics
Information
Abstract
Segmentation is one of the most time-consuming steps within the whole process of Iris Recognition. By means of Fuzzy Mathematical Morphology and Neural Networks, this new algorithm can fulfill the task of isolating the Iris, not only with an acceptable accuracy, but also with a very high improvement in terms of time. Furthermore, this innovative scheme presents an ontology able to decide whether the features can be extracted, based on previous segmentation. This paper provides a detailed explanation of both the problem to be solved and how this new approach meets the required goals. Current Iris Recognition algorithms may benefit from this new approach, and what is more, the essence of the algorithm can be extended to other biometric segmentation procedures.
International
Si
Congress
43rd Annual 2009 IEEE International Carnahan Conference on Security Technology
960
Place
Zurich- Suiza
Reviewers
Si
ISBN/ISSN
978-1-4244-4169-3
Start Date
05/10/2009
End Date
08/10/2009
From page
355
To page
360
Iris Segmentation based on Fuzzy Mathematical Morphology, Neural Networks and Ontologies
Participants
  • Autor: Maria del Carmen Sanchez Avila (UPM)
Research Group, Departaments and Institutes related
  • Creador: Centro o Instituto I+D+i: Centro de Domótica Integral, CEDINT
  • Departamento: Matemática Aplicada a las Tecnologías de la Información
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