Active shape models—their training and application
Computer Vision and Image Understanding
Computers and Electronics in Agriculture
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Computer assisted digital image analysis was performed to investigate the possibility of estimating body weight of live broiler. To achieve the stated objective, 100 Arbor acres broiler chicks were reared under standard rearing condition and 1200 digital images were captured from 20 randomly selected broilers during the 7-42 days growing period. The captured images were analyzed by raster image analysis software (IDRISI 32) to determine the broiler body surface area and developed a linear equation to estimate weights of the broiler from its body surface-area pixels. The developed weight predicted equation based on surface-area pixels was logW=1.060406(logP)+0.173756(logA)-2.029268 (W=estimated body weight, P=surface-area pixels and A=age at weighing) and the degree of goodness of fit of this equation was 0.999. The relative error in weight estimation of broiler chicken by image analysis, expressed in terms of percent error of the residuals from surface-area pixels was in between 0.04 and 16.47. On the other hand, the estimated body weights were not significantly (p0.05) difference from manually measured body weights up to 35 days of age. Thus, the development of a practical imaging system for weighing live broiler is feasible.