Real-time recognition of cattle using animal biometrics

With the advent of efficient recognition techniques, animal biometric systems have gained more proliferation for the identification and monitoring of cattle. A cattle biometric system is a pattern recognition-based system for the identification of livestock. In this paper, we propose a novel muzzle...

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Published in:	Journal of real-time image processing Vol. 13; no. 3; pp. 505 - 526
Main Authors:	Kumar, Santosh, Singh, Sanjay Kumar, Singh, Ravi Shankar, Singh, Amit Kumar, Tiwari, Shrikant
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2017 Springer Nature B.V
Subjects:	Algorithms Animals Biometrics Cameras Cattle Computer Graphics Computer Science Forgery Fraud Identification Image databases Image Processing and Computer Vision Insurance claims Livestock Multimedia Information Systems Pattern Recognition Public domain Real time Registration Semiconductors Signal,Image and Speech Processing Special Issue Paper Surveillance Wireless networks Real-time image processing FLDA FLPP Classification Cattle recognition Feature extraction SVM Animal biometrics Muzzle point
ISSN:	1861-8200, 1861-8219
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Abstract	With the advent of efficient recognition techniques, animal biometric systems have gained more proliferation for the identification and monitoring of cattle. A cattle biometric system is a pattern recognition-based system for the identification of livestock. In this paper, we propose a novel muzzle point recognition based on Fisher locality preserving projection algorithm for the recognition of cattle in real time. We have captured images of animals using a surveillance camera and transferred them to the server by wireless network technology. The major contributions are as follows: (1) preparation of muzzle point database, (2) extraction of the salient set of features using proposed muzzle point recognition approach, and (3) evaluation and comparison analysis of the introduced method and several existing recognition algorithms on a standard benchmark protocol. The efficacy of proposed muzzle point recognition approach for cattle evaluates under identification settings and yields 96.87 % recognition accuracy for identifying individual cattle. The proposed approach also valued the 10.25 sec recognition time for enrollment and identified individual cattle on different sizes of muzzle point images.
AbstractList	With the advent of efficient recognition techniques, animal biometric systems have gained more proliferation for the identification and monitoring of cattle. A cattle biometric system is a pattern recognition-based system for the identification of livestock. In this paper, we propose a novel muzzle point recognition based on Fisher locality preserving projection algorithm for the recognition of cattle in real time. We have captured images of animals using a surveillance camera and transferred them to the server by wireless network technology. The major contributions are as follows: (1) preparation of muzzle point database, (2) extraction of the salient set of features using proposed muzzle point recognition approach, and (3) evaluation and comparison analysis of the introduced method and several existing recognition algorithms on a standard benchmark protocol. The efficacy of proposed muzzle point recognition approach for cattle evaluates under identification settings and yields 96.87 % recognition accuracy for identifying individual cattle. The proposed approach also valued the 10.25 sec recognition time for enrollment and identified individual cattle on different sizes of muzzle point images. With the advent of efficient recognition techniques, animal biometric systems have gained more proliferation for the identification and monitoring of cattle. A cattle biometric system is a pattern recognition-based system for the identification of livestock. In this paper, we propose a novel muzzle point recognition based on Fisher locality preserving projection algorithm for the recognition of cattle in real time. We have captured images of animals using a surveillance camera and transferred them to the server by wireless network technology. The major contributions are as follows: (1) preparation of muzzle point database, (2) extraction of the salient set of features using proposed muzzle point recognition approach, and (3) evaluation and comparison analysis of the introduced method and several existing recognition algorithms on a standard benchmark protocol. The efficacy of proposed muzzle point recognition approach for cattle evaluates under identification settings and yields 96.87% recognition accuracy for identifying individual cattle. The proposed approach also valued the 10.25 sec recognition time for enrollment and identified individual cattle on different sizes of muzzle point images.
Author	Tiwari, Shrikant Singh, Ravi Shankar Kumar, Santosh Singh, Sanjay Kumar Singh, Amit Kumar
Author_xml	– sequence: 1 givenname: Santosh surname: Kumar fullname: Kumar, Santosh email: santosh.rs.cse12@iitbhu.ac.in organization: Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University) – sequence: 2 givenname: Sanjay Kumar surname: Singh fullname: Singh, Sanjay Kumar organization: Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University) – sequence: 3 givenname: Ravi Shankar surname: Singh fullname: Singh, Ravi Shankar organization: Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University) – sequence: 4 givenname: Amit Kumar surname: Singh fullname: Singh, Amit Kumar organization: Department of Computer Science and Engineering, Jaypee University of Information Technology – sequence: 5 givenname: Shrikant surname: Tiwari fullname: Tiwari, Shrikant organization: Department of Computer Science and Engineering, Shri Shankaracharya Technical Campus
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Keywords	Real-time image processing FLDA FLPP Classification Cattle recognition Feature extraction SVM Animal biometrics Muzzle point
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Snippet	With the advent of efficient recognition techniques, animal biometric systems have gained more proliferation for the identification and monitoring of cattle. A...
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SubjectTerms	Algorithms Animals Biometrics Cameras Cattle Computer Graphics Computer Science Forgery Fraud Identification Image databases Image Processing and Computer Vision Insurance claims Livestock Multimedia Information Systems Pattern Recognition Public domain Real time Registration Semiconductors Signal,Image and Speech Processing Special Issue Paper Surveillance Wireless networks
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Title	Real-time recognition of cattle using animal biometrics
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