135845 20260410135822.0 doi 10.1093/jigpal/jzae059 sideral 138864 ART-2025-138864 eng Riego del Castillo, Virginia A non-stressful vision-based method for weighing live lambs 2025 Accurate measurement of livestock weight is a primary indicator in the meat industry to increase the economic gain. In lambs, the weight of a live animal is still usually estimated manually using traditional scales, resulting in a tedious process for the experienced assessor and stressful for the animal. In this paper, we propose a solution to this problem using computer vision techniques; thus, the proposed procedure estimates the weight of a lamb by analysing its zenithal image without interacting with the animal, which speeds up the process and reduces weighing costs. It is based on a data-driven decision support system that uses RGB-D machine vision techniques and regression models. Unlike existing methods, it does not require walk-over-weighing platforms or special and expensive infrastructures. The proposed method includes a decision support system that automatically rejects those images that are not appropriate to estimate the lamb weight. After determining the body contour of the lamb, we compute several features that feed different regression models. Best results were achieved with Extra Tree Regression ($R^{2}$=91.94%), outperforming the existing techniques. Using only an image, the proposed approach can identify with a minimum error the optimal weight of a lamb to be slaughtered, so as to maximise the economic profit. info:eu-repo/grantAgreement/ES/AEI/TED2021-132356B-I00 info:eu-repo/grantAgreement/ES/DGA/GCP-2017-2700 info:eu-repo/semantics/closedAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 0.8 2024 MATHEMATICS 195 / 492 = 0.396 2024 Q2 T2 LOGIC 8 / 27 = 0.296 2024 Q2 T1 MATHEMATICS, APPLIED 235 / 344 = 0.683 2024 Q3 T3 0.264 2024 Philosophy 2024 Q2 Logic 2024 Q3 2.4 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Sánchez-González, Lidia Fernández, Laura Rebollar, Rubén Universidad de Zaragoza (orcid)0000-0002-7891-609X Samperio, Enrique Universidad de Zaragoza 5002 720 Universidad de Zaragoza Dpto. Ingeniería Diseño Fabri. Área Proyectos de Ingeniería 33, 5 (2025), [13 pp.] Log. j. IGPL Logic Journal of the IGPL 1367-0751 970480 http://zaguan.unizar.es/record/135845/files/texto_completo.pdf Versión publicada 1692567 http://zaguan.unizar.es/record/135845/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:135845 articulos driver 2026-04-10-13:53:50 ARTICLE