A machine vision system for early detection and prediction of sick birds: A broiler chicken model

The occurrence of poultry diseases not only affects farm production economics but also leads to poor poultry welfare, food safety concerns, and zoonotic infections. Therefore, timely detection of these diseases is of paramount importance in poultry production. This study proposes a machine vision-ba...

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Bibliographic Details
Published in:Biosystems engineering 2019-12, Vol.188 (C), p.229-242
Main Authors: Okinda, Cedric, Lu, Mingzhou, Liu, Longshen, Nyalala, Innocent, Muneri, Caroline, Wang, Jintao, Zhang, Hailin, Shen, Mingxia
Format: Article
Language:English
Subjects:
Mobility
Posture
Poultry welfare
Shape descriptors
Support vector machine
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Summary:The occurrence of poultry diseases not only affects farm production economics but also leads to poor poultry welfare, food safety concerns, and zoonotic infections. Therefore, timely detection of these diseases is of paramount importance in poultry production. This study proposes a machine vision-based monitoring system for broiler chicken as they walk through a test area. Data were collected from two groups of broilers; control group and treatment group (inoculated intramuscularly with virulent Newcastle disease virus) housed in fully isolated chambers for comparative monitoring. The broilers were monitored by video surveillance for data labelling and depth camera for the automated health status classifier development. Feature variables were extracted based on 2D posture shape descriptors (circle variance, elongation, convexity, complexity, and eccentricity) and mobility feature (walk speed). A statistical analysis of the feature variables established that all investigated features were statistically significant (p
ISSN:1537-5110
1537-5129
DOI:10.1016/j.biosystemseng.2019.09.015