Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extraction of Hybrid Complex Wavelet Features for the Verification of Handwritten Numerals
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Introduction to the Special Issue on Biometrics: Progress and Directions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Assessment of retinal recognition technology as a biometric method for sheep identification
Computers and Electronics in Agriculture
Iris recognition by local extremum points of multiscale Taylor expansion
Pattern Recognition
A new iris segmentation method for non-ideal iris images
Image and Vision Computing
Effect of Severe Image Compression on Iris Recognition Performance
IEEE Transactions on Information Forensics and Security
New Methods in Iris Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Circuits and Systems for Video Technology
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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.