MATEC Web Conf.
Volume 176, 20182018 6th International Forum on Industrial Design (IFID 2018)
|Number of page(s)||4|
|Section||Intelligent Design and Computer Technology|
|Published online||02 July 2018|
Image recognition of individual cow based on SIFT in Lαβ color space
School of Computer Science and Engineering, North Minzu University, No.204 Wen Chang Street,
Yin Chuan, China
Corresponding author : firstname.lastname@example.org
Using image recognition technology to identify individual dairy cattle with her biological features shows strong stability. This kind of non-contact, high precision and low cost individual recognition methods based on image processing are more and more popular recently to replace the electronic tag and ear mark which can hurt the cattle’s psychology and physical health and can affect cattle’s behavior. By comparing the various color space transformations, he proposed a scale-invariant feature transform algorithm based on the Luminace of Lαβ color space. With this algorithm, a biological features recognition and management system of Holstein cow has been developed. The identification accuracy is higher than 98%, which is the best result than all the similar reports for cows’ identification.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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