Meat Quality Detection System Based On Computer Vision Technology

This research provide theoretical basis for the meat quality detection system, a subsystem of the modern agriculture process control system. Subject to the beef quality detection as an example, apply the brightness adjustment algorithm based on the goal of the RGB color space, and automatically adjust the brightness of the image acquisition to minimize brightness factors. Get pixel samples probabilistic neural network training and then pixel sample extraction method used in this study. Through image processing techniques, image segmentation, marbling image and ophthalmoplegia image.7characteristic parameters extracted from the image, and to establish the relationship of the main ingredients of the characteristic parameters of beef marbling level probabilistic neural network model, to achieve the meat quality level of the automatic discrimination system.