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Localization and Segmentation of the Optic Nerve Head in Eye Fundus Images Using Pyramid Representation and Genetic Algorithms

  • José M. Molina
  • Enrique J. Carmona
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6686)

Abstract

This paper proposes an automatic method to locate and segment the optic nerve head (papilla) from eye fundus color photographic images. The method is inspired in the approach presented in [1]. Here, we use a Gaussian pyramid representation of the input image to obtain a subwindow centered at a point of the papillary area. Then, we apply a Laplacian pyramid to this image subwindow and we obtain a set of interest points (IPs) in two pyramid levels. Finally, a two-phase genetic algorithm is used in each pyramid level to find an ellipse containing the maximum number of IPs in an offset of its perimeter and, in this way, to achieve a progressive solution to the ONH contour. The method is tested in an eye fundus image database and, in relation to the method described in [1], the proposed method provides a slightly lower performance but it simplifies the methodology used to obtain the set of IPs and also reduces the computational cost of the whole process.

Keywords

Optic Nerve Head Interest Point Laplacian Pyramid Gaussian Pyramid Pyramid Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • José M. Molina
    • 1
  • Enrique J. Carmona
    • 1
  1. 1.Dpto. de Inteligencia Artificial, ETSI InformáticaUniversidad Nacional de Educación a Distancia (UNED)MadridSpain

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