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Muzzle Point Pattern-Based Techniques for Individual Cattle Identification

Abstract

Animal biometrics-based recognition systems are gradually gaining more proliferation due to their diversity of application and uses. The recognition system is applied for representation, recognition of generic visual features and classification of different species based on their phenotype appearances, the morphological image pattern, and biometric characteristics. The muzzle point image pattern is a primary animal biometric characteristic for the recognition of individual cattle. It is similar to the identification of minutiae points in human fingerprints. This chapter presents an automatic recognition algorithm of muzzle point image pattern of cattle for the identification of individual cattle, verification of false insurance claims, registration, and traceability process. The proposed recognition algorithm uses the texture feature descriptors, such as speeded up robust feature and local binary pattern for the extraction of features from the muzzle point images at different smoothed levels of Gaussian pyramid. The feature descriptors acquired at each Gaussian smoothed level are combined using fusion weighted sum rule method. With a muzzle point image pattern database of 500 cattle, the proposed algorithm yields the desired level of identification accuracy. Moreover, the comparative analysis of experimental results for proposed work and appearance-based face recognition algorithms has been done at each level. The proposed work, therefore, can be a potential approach for the recognition of individual cattle using muzzle point image pattern.

Keywords

  • Animal biometrics
  • Cattle recognition
  • Muzzle point
  • Computer vision
  • Pattern recognition
  • PCA
  • LDA
  • ICA
  • LBP
  • SURF
  • Fusion
  • Texture descriptor

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Correspondence to Santosh Kumar .

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Kumar, S., Singh, S.K., Singh, R., Singh, A.K. (2017). Muzzle Point Pattern-Based Techniques for Individual Cattle Identification. In: Animal Biometrics. Springer, Singapore. https://doi.org/10.1007/978-981-10-7956-6_4

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  • DOI: https://doi.org/10.1007/978-981-10-7956-6_4

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