Automatic evisceration is a very important application technology in the poultry slaughter industry. In this study, a machine-vision-based method of locating the viscera of poultry carcasses is described. Using machine vision, the image recognition system employs a color image segmentation of the HSV (hue, saturation, value) and LAB (Lightness-A-B) color spaces. An active contour segmentation algorithm, threshold segmentation method, and image operations are used to segment the images of viscera of poultry carcasses. Subsequently, the visceral contour is extracted and its position is detected for common poultry from the supermarket, such as Three-Yellow Chicken and Cherry Valley Duck. The identification rates of this visceral contour recognition system were 93.3 and 86.7%, respectively, for each type of poultry, suggesting that the proposed image recognition algorithm could achieve the accuracy required for poultry visceral contour detection. Therefore, the proposed image-processing-based visceral contour recognition method can be applied in poultry processing, improving the production efficiency of Three-Yellow Chicken and Cherry Valley Duck processing and providing more convenient processing services in the poultry industry.
Segmentation of organs was attempted using colour thresholding and active contours in the case of poultry viscera REF .
Poultry carcass visceral contour recognition method using image processing
Journal of Applied Poultry Research
Computer Science