title: Broiler weight estimation based on machine vision and artificial neural network.
abstract: 1. Machine vision and artificial neural network (ANN) procedures were used to estimate live body weight of broiler chickens in 30 1-d-old broiler chickens reared for 42 d. 2. Imaging was performed two times daily. To localise chickens within the pen, an ellipse fitting algorithm was used and the chickens' head and tail removed using the Chan-Vese method. 3. The correlations between the body weight and 6 physical extracted features indicated that there were strong correlations between body weight and the 5 features including area, perimeter, convex area, major and minor axis length. 5. According to statistical analysis there was no significant difference between morning and afternoon data over 42 d. 6. In an attempt to improve the accuracy of live weight approximation different ANN techniques, including Bayesian regulation, Levenberg-Marquardt, Scaled conjugate gradient and gradient descent were used. Bayesian regulation with R2value of 0.98 was the best network for prediction of broiler weight. 7. The accuracy of the machine vision technique was examined and most errors were less than 50 g.
authors.affiliation: a Department of Mechanics of Biosystems Engineering , Faculty of Agricultural Engineering and Rural Development, Ramin Agriculture and Natural Resources University of Khuzestan.
authors.forename: S
authors.initials: S
authors.lastname: Amraei
authors.affiliation: a Department of Mechanics of Biosystems Engineering , Faculty of Agricultural Engineering and Rural Development, Ramin Agriculture and Natural Resources University of Khuzestan.
authors.forename: S
authors.initials: S
authors.lastname: Abdanan Mehdizadeh
authors.affiliation: b Department of Animal Science, Faculty of Animal Science and Food Technology , Ramin Agriculture and Natural Resources University of Khuzestan , Khuzestan , Iran.
authors.forename: S
authors.initials: S
authors.lastname: Salari
mesh_terms: D000822:Animal Husbandry / Q000295:instrumentation / Q000379:methods*; D000818:Animals; D001835:Body Weight; D002645:Chickens / Q000033:anatomy & histology / Q000502:physiology*; D005260:Female; D008297:Male; D016571:Neural Networks, Computer
keywords: Machine vision; artificial neural network; body weight; broiler