Authors: Yue Lu; Xiaofu He; Ying Wen; Patrick S.P. Wang
Addresses: Department of Computer Science and Technology, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China ' Brain Imaging Lab, Department of Psychiatry, Columbia University, 1051 Riverside Drive, New York, NY 10032, USA ' Department of Computer Science and Technology, East China Normal University, 500 Dongchuan Road, Shanghai 200241, China ' College of Computer and Information Science, Northeastern University, 360 Huntington Ave., Boston, MA 02115, USA
Abstract: There is a growing worldwide trend to implement livestock traceability systems. This paper aims to explore how iris analysis and recognition can be utilised on cow identification to enhance cow management in its traceability system. In general, a typical cow identification system based on iris analysis includes iris imaging, iris detection, and recognition. First, the image quality of the captured sequences is assessed and a clear iris image is selected for subsequent process. Second, the inner and outer boundaries of cow iris are fitted respectively as two ellipses based on the edge images during segmentation. Then we can get the segmented cow iris on which normalisation is carried out using geometric method. Finally, 2D complex wavelet transform (2D-CWT) is used to extract local and global characteristics of the cow iris and the phase of the filtered cow iris is encoded as features. Experimental results indicate the effectiveness of the proposed approach.
Keywords: animal identification; cow recognition; iris analysis; iris recognition; iris segmentation; livestock traceability; biometrics; cow identification; image quality; complex wavelet transform; 2D-CWT; cow iris.
International Journal of Biometrics, 2014 Vol.6 No.1, pp.18 - 32
Received: 30 Oct 2012
Accepted: 10 Oct 2013
Published online: 04 Mar 2014 *