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Identification of Cattle Based on Muzzle Point Pattern: A Hybrid Feature Extraction Paradigm

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Abstract

This chapter presents a novel cattle recognition system using hybrid texture feature of muzzle point pattern for identification and classification of cattle breeds. The major contributions of this research are (1) preparation of muzzle point image database, (2) extraction of hybrid texture features of muzzle point images of cattle dataset, (3) classification of cattle using classification models such as K-nearest neighbor (K-NN), Fuzzy-K-NN, Decision Tree (DT), Gaussian Mixture Model (GMM), Probabilistic Neural Network (PNN), Multilayer Perceptron(MLP), and Naive Bays. In addition, the proposed approach is validated by achieving the state-of-the-art accuracy on muzzle point image database of cattle with standard identification settings.

Keywords

  • Animal biometrics
  • Muzzle pattern
  • Cattle recognition
  • Features extraction
  • Classification

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Kumar, S., Singh, S.K., Singh, R., Singh, A.K. (2017). Identification of Cattle Based on Muzzle Point Pattern: A Hybrid Feature Extraction Paradigm. In: Animal Biometrics. Springer, Singapore. https://doi.org/10.1007/978-981-10-7956-6_5

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  • DOI: https://doi.org/10.1007/978-981-10-7956-6_5

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