Eye features are one of the most important clues for many computer vision applications. In this paper, an efficient method to automatically extract eye features is presented. The extraction is highly based on the usage of the common knowledge about face and eye structure. With the assumption of frontal face images, firstly coarse eye regions are extracted by removing skin pixels in the upper part of the face. Then, iris circle position and radius are detected by using Hough transform in a coarse-to-fine fashion. In the final step, edges created by upper and lower eyelids are detected and polynomials are fitted to those edges so that their intersection points are labeled as eye corners. The algorithm is experimented on the Bosphorus database and the obtained results demonstrate that it can locate eye features very accurately. The strength of the proposed method stems from its reproducibility due to the utilization of simple and efficient image processing methods while achieving remarkable results without any need of training.


Eye features extraction iris eye corners and eyelids 


  1. 1.
    Brunelli, R., Poggio, T.: Face recognition: features versus templates. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(10), 1042–1052 (1993)CrossRefGoogle Scholar
  2. 2.
    Zheng, Z., Yang, J., Yang, L.: A robust method for eye features extraction on color image. Pattern Recognition Letters 26(14), 167–8655 (2005) ISSN 0167-8655CrossRefGoogle Scholar
  3. 3.
    Khairosfaizal, W.M.K.W.M., Nor’aini, A.J.: Eyes detection in facial images using Circular Hough Transform. In: 5th International Colloquium on Signal Processing & Its Applications, CSPA 2009, March 6-8, pp. 238–242 (2009)Google Scholar
  4. 4.
    Pardas, M.: Extraction and tracking of the eyelids. In: Proceedings of 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2000, vol. 6, 4 pp. 2357–2360 (2000)Google Scholar
  5. 5.
    Park, C.W., Kwak, J.M., Park, H., Moon, Y.S.: An Effective Method for Eye Detection Based on Texture Information. In: International Conference on Convergence Information Technology 2007, November 21-23, pp. 586–589 (2007)Google Scholar
  6. 6.
    Guan, Y.: Robust Eye Detection from Facial Image based on Multi-cue Facial Information. In: IEEE International Conference on Control and Automation, ICCA 2007, May 30-June 1, pp. 1775–1778 (2007)Google Scholar
  7. 7.
    Kuo, P., Hannah, J.: An improved eye feature extraction algorithm based on deformable templates. In: IEEE International Conference on Image Processing, ICIP 2005, September 11-14, vol. 2, p. II-1206-9 (2005)Google Scholar
  8. 8.
    Wang, P., Green, M.B., Ji, Q., Wayman, J.: Automatic Eye Detection and Its Validation. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPR Workshops, June 25, pp. 164–164 (2005)Google Scholar
  9. 9.
    Zhou, Z.-H., Geng, X.: Projection functions for eye detection. Pattern Recognition 37(5), 1049–1056 (2004) ISSN 0031-3203zbMATHCrossRefGoogle Scholar
  10. 10.
    Feng, G.: Variance projection function and its application to eye detection for human face recognition. Pattern Recognition Letters 19(9), 899–906 (1998)CrossRefGoogle Scholar
  11. 11.
    Haiying, X., Guoping, Y.: A Novel Method for Eye Corner Detection Based on Weighted Variance Projection Function. In: 2nd International Congress on Image and Signal Processing, CISP 2009, October 17-19, pp. 1–4 (2009)Google Scholar
  12. 12.
    Xu, C., Zheng, Y., Wang, Z.: Semantic feature extraction for accurate eye corner detection. In: 19th International Conference on Pattern Recognition, ICPR 2008, December 8-11, pp. 1–4 (2008)Google Scholar
  13. 13.
    Yin, L., Basu, A.: Integrating active face tracking with model based coding. Pattern Recognition Letters 20(6), 651–657 (1999) ISSN 0167-8655CrossRefGoogle Scholar
  14. 14.
    Vezhnevets, V., Degtiareva, A.: Robust and Accurate Eye Contour Extraction. In: Proc. Graphicon 2003, Moscow, Russia, September 2003, pp. 81–84 (2003)Google Scholar
  15. 15.
    Tse, K.W., Lau, W.H., Leung, S.H., Liew, A.W.C.: Eye extraction using spatial fuzzy clustering method. In: Proceedings of 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering TENCON 2002, October 2002, vol. 1, pp. 515–518 (2002)Google Scholar
  16. 16.
    MATLAB Central Program for Color Image Segmentation – Athi Narayanan S, K.S.R. College of Engineering, Erode, Tamil Nadu, India,
  17. 17.
    Savran, N., Alyüz, H., Dibeklioğlu, O., Çeliktutan, B., Gökberk, B., Sankur, L.A.: Bosphorus Database for 3D Face Analysis. In: The First COST 2101 Workshop on Biometrics and Identity Management (BIOID 2008), May 2008, Roskilde University, Denmark (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Nesli Erdogmus
    • 1
  • Jean-Luc Dugelay
    • 1
  1. 1.Eurecom, Multimedia Communications DepartmentSophia AntipolisFrance

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