Normalizing Human Ear in Proportion to Size and Rotation

There are always two main problems in identification of human beings through their ear images: 1- If distances of the individual from camera changes, the sizes of ears in the saved images are varied in proportion to this distance. 2- If head of people in taken images is tilted upwards or downwards, this causes ear images of these people rotate in proportion to saved ear images in database. In both of these cases, all identification systems do not work properly. In this article, we proposed a new method for normalizing human ear images by detecting the rotation and scaling variation, and normalizing the ear images accordingly. Our proposed method works well on all ear databases and all ear images (either left or right) which have been taken from front side of the ears. Our method provides high performance to the biometric identification systems to identify human being, even when the images of human ears are taken from long distance with small scale.

[1]  Zhi-Chun Mu,et al.  A novel approach for ear recognition based on ICA and RBF network , 2005, 2005 International Conference on Machine Learning and Cybernetics.

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

[3]  Alphonse Bertillon,et al.  La photographie judiciaire, avec un appendice sur la classification et l'identification anthropométriques , 1890 .

[4]  Zhengguang Xu,et al.  Using Ear Biometrics for Personal Recognition , 2005, IWBRS.

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

[6]  Phalguni Gupta,et al.  A Simple Geometric Approach for Ear Recognition , 2006, 9th International Conference on Information Technology (ICIT'06).

[7]  B. Moreno,et al.  On the use of outer ear images for personal identification in security applications , 1999, Proceedings IEEE 33rd Annual 1999 International Carnahan Conference on Security Technology (Cat. No.99CH36303).

[8]  Wilhelm Burger,et al.  Ear biometrics in computer vision , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[9]  Sharath Pankanti,et al.  Advances in Biometric Person Authentication, International Workshop on Biometric Recognition Systems, IWBRS2005, Beijing, China, October 22-23, 2005, Proceedings , 2005, IWBRS.

[10]  Mark S. Nixon,et al.  Force field feature extraction for ear biometrics , 2005, Comput. Vis. Image Underst..