Abstract
Localization of ear in the side face images is a fundamental step in the development of ear recognition based biometric systems. In this paper, a well-known distance measure termed as modified Hausdorff distance (MHD) is proposed for automatic ear localization. We introduced the MHD to decrease the effect of outliers and allowing it more suitable for detection of ear in the side face images. The MHD uses coordinate pairs of edge pixels derived from ear template and skin regions of the side face image to locate the ear portion. To detect ears of various shapes, ear template is created by considering different structure of ears and resized it automatically for the probe image to find exact location of ear. The CVL and UND-E database have side face images with different poses, inconsistent background and poor illumination utilized to analyse the effectiveness of the proposed algorithm. Experimental results reveal the strength of the proposed technique is invariant to various poses, shape, occlusion, and noise.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
A. Bertillon, La Photographie Judiciaire: Avec Un Appendice Sur La Classification Et L’Identification Anthropometriques, Gauthier-Villars, Paris, (1890).
A.V. Iannarelli, “Ear identification,” in Proceedings of International Workshop Frontiers in Handwriting Recognition, Paramont Publishing Company, Freemont, California, (1989).
M. Burge and W. Burger, “Ear biometrics in computer vision,” In Proceedings of ICPR, vol. 2, pp. 822–826, (2000).
Michal Choras, “Ear Biometrics Based on Geometrical Feature Extraction,” Lecture Notes in Computer Science, pp. 51–61, (2004).
D. J. Hurley, M. S. Nixon, and J. N. Carter, “Force Field Feature Extraction for Ear Biometrics,” Computer Vision and Image Understanding, vol. 98, pp. 491–512, (2005).
L. Alvarez, E. Gonzalez, and L. Mazorra “Fitting ear contour using an ovoid model,” In Proceedings of ICCST, pp. 145–148, (2005).
S. Ansari and P. Gupta, “Localization of ear using outer helix curve of the ear,” In Proceedings of ICCTA, pp. 688–692, (2007).
L. Yuan and Z.-C. Mu, “Ear detection based on skin-color and contour information,” In Proceedings of ICMLC, vol. 4, pp. 2213–2217, (2007).
A. Sana, P. Gupta, and R. Purkait, “Ear biometric: A new approach,” In Proceedings of ICAPR, pp. 46–50, (2007).
S.M.S. Islam, M. Bennamoun, and R. Davies, “Fast and fully automatic ear detection using cascaded adaboost,” In Proceedings of IEEE Workshop on Applications of Computer Vision (WACV’ 08), pp. 1–6, (2008).
Surya Prakash, J. Umarani, and P. Gupta, “Ear localization from side face images using distance transform and template matching,” in Proceedings of IEEE Int’l Workshop on Image Proc. Theory, Tools and Application, (IPTA), Sousse, Tunisia, pp. 1–8, (2008).
Surya Prakash, J. Umarani, and P. Gupta, “A skin-color and template based technique for automatic ear detection,” in Proceedings of ICAPR, India, pp. 213–216, (2009).
Surya Prakash, J. Umarani, and P. Gupta, “Connected Component Based Technique for Automatic Ear Detection,” in Proceedings of the 16th IEEE Int’l Conference of Image Processing (ICIP), Cairo, Egypt, pp. 2705–2708, (2009).
J. Cai, and A. Goshtasby, “Detecting human faces in color images,” Image and Vision Computing, 18(1), pp. 63–75, (1999).
G. Wyszecki and W.S. Styles, “Color Science: Concepts and Methods, Quantitative Data and Formulae,” second edition, John Wiley & Sons, New York (1982).
D.P. Huttenlocher, G.A. Klanderman, W.J. Rucklidge, “Comparing images using the Hausdorff distance,” IEEE Trans. Pattern Anal. Mach. Intell. 850–863, (1993).
M.P. Dubuisson and A.K. Jain, “A modified Hausdorff distance for object matching,” In ICPR94, Jerusalem, Israel, pp. A:566–568, (1994).
J. Canny, “A computational approach to edge detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 679–698, (1986).
Peter Peer, “CVL Face Database,” Available: http://www.lrv.fri.uni-lj.si/facedb.html.
University of Notre Dame Profile Face Database, Collection E, http://www.nd.edu/~cvrl/CVRL/DataSets.html.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Science+Business Media Singapore
About this paper
Cite this paper
Sarangi, P.P., Panda, M., Mishra, B.S.P., Dehuri, S. (2017). An Automated Ear Localization Technique Based on Modified Hausdorff Distance. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_21
Download citation
DOI: https://doi.org/10.1007/978-981-10-2107-7_21
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-2106-0
Online ISBN: 978-981-10-2107-7
eBook Packages: EngineeringEngineering (R0)