An Improved Bovine Iris Segmentation Method

Zhongliang Luo; Jingguo Dai; Yingbiao Jia; Jiazhong He

doi:10.1051/matecconf/201926703002

All issues

Volume 267 (2019)

MATEC Web Conf., 267 (2019) 03002

References

Open Access

Issue		MATEC Web Conf. Volume 267, 2019 2018 2^nd AASRI International Conference on Intelligent Systems and Control (ISC 2018)


Article Number		03002
Number of page(s)		5
Section		Biological and Chemical Engineering
DOI		https://doi.org/10.1051/matecconf/201926703002
Published online		11 February 2019

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[1] L. D. Zhao, S.N. Sun, Q. Kong, Food traceability system based on iris recognition middleware. Icic Express Letters, 2009, 3(4):1251-1256. [Google Scholar]

[2] J. Velez, A. Sanchez, J. Sanchez, Beef identification in industrial Slaughter houses using machine vision techniques. Spanish Journal of Agricultural Research, 2013, 11(4): 945-957 [CrossRef] [Google Scholar]

[3] S. Ahmed, T. Gaber, A. Tharwat, Muzzle-Based Cattle Identification Using Speed up Robust Feature Approach[C]// Intelligent Networking and Collaborative Systems, 2015 International Conference on. IEEE, 2015. 99-104 [Google Scholar]

[4] S. Ammendrup, Fussel A. E. Legislative requirements for the identification and traceability of farm animals within the European union[J]. Scientific and Technical Review, 2001, 20(2): 437-443 [Google Scholar]

[5] Z.L. Luo, Y.B. Jia, The bovine iris location method based on dynamic contour tracking and least square principle. International Journal of Signal Processing, Image Processing and Pattern Recognition, 2016, 9(7): 275-284 [CrossRef] [Google Scholar]

[6] U. Gonzales Barren, G. Corkery, B. Barry. Assessment of retinal recognition technology as a biometric method for sheep identification [J]. Computer and Electronics in Agriculture, 2008, 60(2): 156-166 [CrossRef] [Google Scholar]

[7] J.S. Zhang, H. Zhou, Comparisons on animal ID technology [J]. Chinese Journal of Animal Science, 2008, 44(11):55-58. [Google Scholar]

[8] S. Masahiko, Y. Osamu, A horse identification system using biometrics[J]. Systems and Computers in Japan, 2001, 32(14): 12-23 [Google Scholar]

[9] A. Allen, B. Golden, M. Taylor. Evaluation of retinal imaging technology for the biometric identification of bovine animals in Northern Ireland [J]. Livestock Science, 2008, 116(3):42-52 [CrossRef] [Google Scholar]

[10] D.W. Sheng, X.F. He, Y. Lu. A cattle iris segmentation method aased on keast square principle[J]. Journal of Image and Graphics, 2009, 14(10): 2122-2126 [Google Scholar]

[11] Li Chao Zhao Lindu. Research on Cattle Iris Localization Algorithm and Its Application in Meat Food Tracking and Traceability System[J]. China Safety Science Journal, 2011, 21(3):124-129 [Google Scholar]

[12] R.P. Wildes, Iris recognition: An emerging biometric technology [C] // Proceeding of the IEEE, 1997, 85(9): 1348-1363 [CrossRef] [Google Scholar]

[13] J. Daugman, New methods in iris recognition.[J]. IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man & Cybernetics Society, 2007, 37(5):1167-75. [CrossRef] [Google Scholar]

[14] M. Nirali Bhagwagar, A. Yagnik Rathod. A Survey on iris recognition for authentication [J]. International Journal of Technical Research and Applications, 2015, 3(2):148-151. [Google Scholar]

[15] Kass M., Witkin A., Terzopoulos D. Snakes: Active contour models [J]. International Journal of Computer Vision, 1988, 1(4):32l-331. [Google Scholar]

[16] Caselles V., Kimmel R., Sapiro G.. Geodesic active contours [J]. International Journal of Computer Vision, 1997, 22(1):61-79. [CrossRef] [Google Scholar]

[17] C.M. Li, C.Y. Xu, C.F. Gui, Level set evolution without reinitialization: A new variational formulation[C]//. Proceeding of the IEEE Computer Society Conference 0n Computer Vision and Pattern Recognition, 2005, 430-436 [Google Scholar]

[18] B. Yan, B. Wang, Y. Li, Optimal ellipse fitting method based on least-square principle [J]. Journal of Beijing University of Aeronautics & Astronautics, 2008, 34(3): 295-298. [Google Scholar]

[19] S. Gayathri, N. Mohanapriya, Survey on contrast enhancement techniques, International Journal of Advanced Research in Computer and Communication Engineering, 2013, 2(11) :4176–4180. [Google Scholar]