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

  • P. M. D. S. Pallawala
  • Wynne Hsu
  • Mong Li Lee
  • Kah-Guan Au Eong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3022)


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.


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.


  1. 1.
    Aguado, A.S., Nixon, M.S.: A New Hough Transform Mapping for Ellipse Detection. Technical Report, University of Southampton (1995)Google Scholar
  2. 2.
    Balo, K.P., Mihluedo, H., Djagnikpo, P.A., Akpandja, M.S., Bechetoille, A.: Correlation between Neuroretinal Rim and Optic Disc Areas in Normal Melanoderm and Glaucoma Patients. J. Fr. Ophtalmol. 23 (2000)Google Scholar
  3. 3.
    Bonomi, L., Orzalesi, N.: Glaucoma: Concepts in Evolution. Morphometric and Functional Parameters in the Diagnosis and Management of Glaucoma. Kugler Publications, New York (1991)Google Scholar
  4. 4.
    Fitzgibbon, A., Pilu, M., Fisher, R.B.: Direct Least Square Fitting of Ellipses. IEEE Tran. on Pattern Analysis & Machine Intelligence 21 (1999)Google Scholar
  5. 5.
    Hamilton, A.M.P., Ulbig, M.W., Polkinghorne, P.: Management of Diabetic Retinopathy (1996) Google Scholar
  6. 6.
    Hsu, W., Pallawala, P.M.D.S., Lee, M.L., Au-Eong, K.G.: The Role of Domain Knowledge in the Detection of Retinal Hard Exudates. In: IEEE Conf. on Computer Vision and Pattern Recognition (2001)Google Scholar
  7. 7.
    Kass, A., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. Int. Journal of Computer Vision (1988)Google Scholar
  8. 8.
    Lalonde, M., Beaulieu, M., Gagnon, L.: Fast and Robust Optic Disc Detection Using Pyramidal Decomposition and Hausdorff-Based Template Matching. IEEE Trans. on Medical Imaging (2001)Google Scholar
  9. 9.
    Larsen, H.W.: Manual and Color Atlas of the Ocular Fundus (1976)Google Scholar
  10. 10.
    Lee, S., Brady, M.: Optic Disc Boundary Detection. In: British Machine Vision Conference (1989)Google Scholar
  11. 11.
    Leroy, B., Herlin, I.L., Cohen, L.D.: Multi-Resolution Algorithms for Active Contour Models. In: Int. Conf. on Analysis and Optimization of Systems (1996)Google Scholar
  12. 12.
    Lewis, A., Knowles, G.: Image Compression Using the 2-D Wavelet. IEEE Trans. on Image Processing (1992)Google Scholar
  13. 13.
    Li, H., Chutatape, O.: Automatic Location of Optic Disc in Retinal Images. In: Int. Conf. on Image Processing (2001)Google Scholar
  14. 14.
    Mendels, F., Heneghan, C., Harper, P.D., Reilly, R.B., Thiran, J.-P.: Extraction of the Optic Disc Boundary in Digital Fundus Images. In: First Joint BMES/EMBS Conf. Serving Humanity, Advancing Technology (1999)Google Scholar
  15. 15.
    Mendels, F., Heneghan, C., Thiran, J.-P.: Identification of the Optic Disc Boundary in Retinal Images Using Active Contours. In: Irish Machine Vision and Image Processing Conf. (1999)Google Scholar
  16. 16.
    Morris, D.T., Donnison, C.: Identifying the Neuro-Retinal Rim Boundary Using Dynamic Contours. Image and Vision Computing 17 (1999)Google Scholar
  17. 17.
    Park, H.W., Schoepflin, T., Kim, Y.: Active Contour Model with Gradient Directional Information: Directional Snake. IEEE Trans. On Circuits and Systems for Video Technology (2001)Google Scholar
  18. 18.
    Sinthanayothin, C., Boyce, J.F., Cook, H.L., Williamson, T.H.: Automated Localization of Optic Disc, Fovea and Retinal Blood Vessels from Digital Color Fundus Images. British Journal of Ophthalmology (1999)Google Scholar
  19. 19.
    Wang, H., Hsu, W., Goh, K.G., Lee, M.L.: An Effective Approach to Detect Lesions in Color Retinal Images. In: IEEE Conf. on Computer Vision and Pattern Recognition (2000)Google Scholar
  20. 20.
    World Health Organization Fact Sheet No. 138 (2002)Google Scholar
  21. 21.
    Xu, C., Prince, J.L.: Generalized Gradient Vector Flow External Forces for Active Contours. Signal Processing (1998)Google Scholar
  22. 22.
    Xu, C., Prince, J.L.: Snakes, Shapes, and Gradient Vector Flow. IEEE Trans. on Image Processing (1988)Google Scholar
  23. 23.
    Xu, C., Yezzi, A., Prince, J.L.: On the Relationship Between Parametric and Geometric Active Contours. In: 34th Asimolar Conf. on Signals, Systems, and Computers (2000)Google Scholar
  24. 24.
    Yogesan, K., Barry, C.J., Jitskaia, L., Eikelboom, M.W.H., House, P.H., Saarloos, P.P.V.: Software for 3-D Visualization/Analysis of Optic-Disc Images. IEEE Engineering in Medicine and Biology (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • P. M. D. S. Pallawala
    • 1
  • Wynne Hsu
    • 1
  • Mong Li Lee
    • 1
  • Kah-Guan Au Eong
    • 2
    • 3
  1. 1.School of Computing, NationalUniversity of SingaporeSingapore
  2. 2.Ophthalmology and Visual SciencesAlexandra HospitalSingapore
  3. 3.The Eye InstituteNational Healthcare GroupSingapore

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