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Sensors 2018, 18(1), 132; https://doi.org/10.3390/s18010132

Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations

1
Department of Human Sciences and Quality of Life Promotion, Università Telematica San Raffaele Roma, Via di Val Cannuta 247, 00166 Rome, Italy
2
Department of Veterinary Medicine, Università degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy
3
Animal & Veterinary Sciences, Scotland’s Rural College, Roslin Institute Building, Easter Bush, Midlothian, Edinburgh EH9 3JG, Scotland, UK
4
Department of Health, Animal Science and Food Safety (VESPA), Università degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy
*
Author to whom correspondence should be addressed.
Received: 15 November 2017 / Revised: 29 December 2017 / Accepted: 3 January 2018 / Published: 5 January 2018
(This article belongs to the Section Physical Sensors)
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Abstract

Free range systems can improve the welfare of laying hens. However, the access to environmental resources can be partially limited by social interactions, feeding of hens, and productivity, can be not stable and damaging behaviors, or negative events, can be observed more frequently than in conventional housing systems. In order to reach a real improvement of the hens’ welfare the study of their laying performances and behaviors is necessary. With this purpose, many systems have been developed. However, most of them do not detect a multiple occupation of the nest negatively affecting the accuracy of data collected. To overcome this issue, a new “nest-usage-sensor” was developed and tested. It was based on the evaluation of thermografic images, as acquired by a thermo-camera, and the performing of patter recognitions on images acquired from the nest interior. The sensor was setup with a “Multiple Nest Occupation Threshold” of 796 colored pixels and a template of triangular shape and sizes of 43 × 33 pixels (high per base). It was tested through an experimental nesting system where 10 hens were reared for a month. Results showed that the evaluation of thermografic images could increase the detection performance of a multiple occupation of the nest and to apply an image pattern recognition technique could allow for counting the number of hens in the nest in case of a multiple occupation. As a consequence, the accuracy of data collected in studies on laying performances and behaviors of hens, reared in a free-range housing system, could result to be improved. View Full-Text
Keywords: double nest occupation; infrared camera; imaging analysis; image pattern matching; laying hens’ performance and behavior double nest occupation; infrared camera; imaging analysis; image pattern matching; laying hens’ performance and behavior
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Zaninelli, M.; Redaelli, V.; Luzi, F.; Mitchell, M.; Bontempo, V.; Cattaneo, D.; Dell’Orto, V.; Savoini, G. Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations. Sensors 2018, 18, 132.

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