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Missed, swapped, false insurance claimed and reallocation of cattle at slaughter houses is global problems throughout the world. Only few researches have been done so far to solve such major problems. Traditional identification approaches and non-biometrics techniques have such severe problems due to their own boundaries and limitations for the registration and traceability of cattle. These techniques are not able to provide a competent level of security to livestock/cattle. Therefore, cattle identification needs an innovative research for the development of efficient, scalable, affordable, non-invasive, automatic recognition systems for better registration, traceability and security of livestock/cattle. In this paper, an attempt has been made to solve the above problems by using computer vision approaches for cattle recognition using their facial images. The major contributions of this research are in three folds: firstly, the preparations of a facial images database of cattle, secondly, the extraction of set of discriminatory features from the database and implementation of computer vision based face recognition algorithms for recognizing cattle and finally, the experimental results and discussion of face recognition algorithms. Thus, this paper presents a comprehensive review of the performances of various computer vision and pattern recognition approaches for the application of cattle face recognition.

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Correspondence to Shrikant Tiwari.

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Kumar, S., Tiwari, S. & Singh, S.K. Face Recognition of Cattle: Can it be Done?. Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci. 86, 137–148 (2016).

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