Human ear recognition using geometric features

Biometrics includes the study of automatic methods for distinguishing human beings based on physical or behavioral traits. Finding good biometric methods has been researched extensively in recent years. Among several biometric features, ear is quite stable because it does not vary with age and emotion. The ear recognition works based on the height of the ear, reference line cut point and corresponding angles. The study is performed on the ear in random orientation and shows a greater accuracy than existing dominant approach. The recognition accuracy is increased by removing the noise in captured ear images and developing new methodologies to work with online images.

[1]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Karim Faez,et al.  A New Segmentation Approach for Ear Recognition , 2008, ACIVS.

[3]  Mohamed Abdel-Mottaleb,et al.  Human Ear Recognition from Face Profile Images , 2006, ICB.

[4]  L. Mazorra,et al.  Fitting ear contour using an ovoid model , 2005, Proceedings 39th Annual 2005 International Carnahan Conference on Security Technology.

[5]  M. Choraś,et al.  Perspective methods of biometric human identification , 2008, New Trends in Audio and Video / Signal Processing Algorithms, Architectures, Arrangements, and Applications SPA 2008.

[6]  Phalguni Gupta,et al.  Localization of Ear Using Outer Helix Curve of the Ear , 2007, 2007 International Conference on Computing: Theory and Applications (ICCTA'07).

[7]  Hui Chen,et al.  Shape Model-Based 3D Ear Detection from Side Face Range Images , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[8]  Mark S. Nixon,et al.  A novel ray analogy for enrolment of ear biometrics , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[9]  Phalguni Gupta,et al.  An efficient technique for ear detection in 3D: Invariant to rotation and scale , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[10]  Michal Choras,et al.  Ear Biometrics Based on Geometrical Feature Extraction , 2005, Progress in Computer Vision and Image Analysis.

[11]  Mohammed Bennamoun,et al.  Efficient Detection and Recognition of 3D Ears , 2011, International Journal of Computer Vision.

[12]  M. S. Sadi,et al.  2D human-ear recognition using geometric features , 2012, 2012 7th International Conference on Electrical and Computer Engineering.

[13]  Hui Chen,et al.  Contour Matching for 3D Ear Recognition , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.