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European Conference on Computer Vision

ECCV 2004: Computer Vision - ECCV 2004 pp 139–151Cite as

Automated Optic Disc Localization and Contour Detection Using Ellipse Fitting and Wavelet Transform

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNCS,volume 3022)

Abstract

Optic disc detection is important in the computer-aided analysis of retinal images. It is crucial for the precise identification of the macula to enable successful grading of macular pathology such as diabetic maculopathy. However, the extreme variation of intensity features within the optic disc and intensity variations close to the optic disc boundary presents a major obstacle in automated optic disc detection. The presence of blood vessels, crescents and peripapillary chorioretinal atrophy seen in myopic patients also increase the complexity of detection. Existing techniques have not addressed these difficult cases, and are neither adaptable nor sufficiently sensitive and specific for real-life application. This work presents a novel algorithm to detect the optic disc based on wavelet processing and ellipse fitting. We first employ Daubechies wavelet transform to approximate the optic disc region. Next, an abstract representation of the optic disc is obtained using an intensity-based template. This yields robust results in cases where the optic disc intensity is highly non-homogenous. Ellipse fitting algorithm is then utilized to detect the optic disc contour from this abstract representation. Additional wavelet processing is performed on the more complex cases to improve the contour detection rate. Experiments on 279 consecutive retinal images of diabetic patients indicate that this approach is able to achieve an accuracy of 94% for optic disc detection.

Keywords

  • Optic Disc
  • Active Contour
  • Retinal Image
  • Active Contour Model
  • Daubechies Wavelet

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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Author information

Authors and Affiliations

  1. School of Computing, National, University of Singapore, Singapore

    P. M. D. S. Pallawala, Wynne Hsu & Mong Li Lee

  2. Ophthalmology and Visual Sciences, Alexandra Hospital, Singapore

    Kah-Guan Au Eong

  3. The Eye Institute, National Healthcare Group, Singapore

    Kah-Guan Au Eong

Authors
  1. P. M. D. S. Pallawala
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  2. Wynne Hsu
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  3. Mong Li Lee
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  4. Kah-Guan Au Eong
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Editor information

Editors and Affiliations

  1. Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University, Prague 6, Czech Republic

    Tomás Pajdla

  2. Center for Machine Perception, Dept. of Cybernetics, Faculty of Elec. Eng., Czech Technical University in Prague, Karlovo nám. 13, 121 35, Prague, Czech Rep.

    Jiří Matas

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© 2004 Springer-Verlag Berlin Heidelberg

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Pallawala, P.M.D.S., Hsu, W., Lee, M.L., Eong, KG.A. (2004). Automated Optic Disc Localization and Contour Detection Using Ellipse Fitting and Wavelet Transform. In: Pajdla, T., Matas, J. (eds) Computer Vision - ECCV 2004. ECCV 2004. Lecture Notes in Computer Science, vol 3022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24671-8_11

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  • DOI: https://doi.org/10.1007/978-3-540-24671-8_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21983-5

  • Online ISBN: 978-3-540-24671-8

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