Milad Lankarany, Alireza Ahmadyfard



Ear segmentation is considered as the first step of all ear biometrics systems while the objective in separating the ear from its surrounding backgrounds is to improve the capability of automatic systems used for ear recognition. To meet this objective in the context of ear biometrics a new automatic algorithm based on topographic labels is presented here. The proposed algorithm contains four stages. First we extract topographic labels from the ear image. Then using the map of regions for three topographic labels namely, ridge, convex hill and convex saddle hill we build a composed set of labels. The thresholding on this labelled image provides a connected component with the maximum number of pixels which represents the outer boundary of the ear. As well as addressing faster implementation and brightness insensitivity, the technique is also validated by performing completely successful ear segmentation tested on “USTB” database which contains 308 profile view images of the ear and its surrounding backgrounds.


  1. Ping Yan and Kevin W.Bowyer “Biometric Recognition Using 3-D Ear Shape”, IEEE Trans. PAMI, VOL. 29, NO. 8, 2007
  2. B. Bhanu and H. Chen, “Human Ear Recognition in 3D,” Proc.Workshop Multimodal User Authentication, pp. 91-98, 2003.
  3. D. Hurley, M. Nixon, and J. Carter, “Force Field Energy Functionals for Image Feature Extraction,” Image and Vision Computing J., vol. 20, pp. 429-432, 2002.
  4. H. Chen and B. Bhanu, “Human Ear Detection from Side Face Range Images,” Proc. Int'l Conf. Image Processing, pp. 574-577, 2004.
  5. H. Chen and B. Bhanu, “Contour Matching for 3D Ear Recognition,” Proc. Seventh IEEE Workshop Application of Computer Vision,pp. 123-128, 2005.
  6. K. Messer, J. Matas, J. Kittler, J. Luettin, and G. Maitre, “XM2VTSDB: The Extended M2VTS Database,”Audio and Video-Based Biometric Person Authentication, pp. 72-77, 1999.
  7. M. Choras, “Ear Biometrics Based on Geometrical Feature Extraction,” Electronic Letters on Computer Vision and Image Analysis, vol. 5, pp. 84-95, 2005.
  8. M. Choras, “Further Developments in Geometrical Algorithms for Ear Biometrics,” Proc. Fourth Int'l Conf. Articulated Motion and Deformable Objects, pp. 58-67, 2006.
  9. B. Luo, A.D. Cross, E.R. Hancock, “Corner detection via topographic analysis of vector potential”, Pattern Recognition Letter. 20 (6) (1999) 635-650.
  10. N. Ahuja, “A transform for multiscale image segmentation by integrated edge and region detection”, IEEE Trans. PAMI 18 (12) (1996) 1211-1235.
  11. N. Ahuja, J.H. Chuang, Shape representation using a generalized potential field model, IEEE Trans. PAMI 19 (2) (1997) 169-176.
  12. Li Yuan, Zhichun Mu, Zhengguang Xu, “Using Ear Biometrics for Personal Recognition”, IWBRS 2005, Beijing, China, October 2005, 221-228.
  13. C. Xu, J.L. Prince, “Gradient vector flow: a new external force for snakes”, in: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 1997, pp. 66-71.
  14. R. M. Haralick. L. T. Watson, and T. J. Laffey, "The topographic primal sketch," Int. J . Robotics Res. vol. 2, pp. 50-72, 1983.
  15. J. Wang, and L. Yin, "Static topographic modeling for facial expression recognition and analysis," Computer Vision and Image Understanding Journal, vol. 108, pp. 19-34, October 2007.
  16. L. Wang, and T. Pavlidis."Direct Gray-Scale Extraction of Features for Character Recognition",IEEE Trans. PAMI. vol. 15, no. 10, pp.1053-1067, October 1993.

Paper Citation

in Harvard Style

Lankarany M. and Ahmadyfard A. (2009). EAR SEGMETATION USING TOPOGRAPHIC LABELS . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 186-191. DOI: 10.5220/0001797601860191

in Bibtex Style

author={Milad Lankarany and Alireza Ahmadyfard},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},

in EndNote Style

JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
SN - 978-989-8111-69-2
AU - Lankarany M.
AU - Ahmadyfard A.
PY - 2009
SP - 186
EP - 191
DO - 10.5220/0001797601860191