Computer vision algorithm for the identification of free-range chickens
Year: 2025
Type: article
Abstract: ABSTRACT The increase in the number of free-range breeders in Canela-Preta strengthens the Brazilian poultry industry, mainly in terms of biosafety, health and quality of the animals. Therefore, it is necessary to identify these chickens using modern and non-invasive techniques, thus, this study aimed to develop a computer vision algorithm based on artificial intelligence to identify Canela-Preta chickens using images. An accuracy rate of 86.54% and similarity of 99.58% were obtained using YOLO (you only look once) for detection and template matching for identification. It was concluded that the individual identification of free-range Canela-Preta chickens using the proposed methodology was accurate.
Authors: J.S. Moura, D.A. Carvalho, M.J.O. Almeida, J.L.R. Sarmento, F.C.B. Sousa, R.R.V. Silva, O.P. Silva Neto, N.P.S. Santos
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $800
OpenAlex ID: W4415588596