Grading meat quality by image processing

Abstract We study the implementation of a meat-quality grading system, using the concept of the “marbling score”, as well as image processing, neural network techniques and multiple regression analysis. The marbling score is a measure of the distribution density of fat in the rib-eye region. We identify five features used for grading meat images. For the evaluation of the five features, we propose a method of image binarization using a three-layer neural network developed on the basis of inputs given by a professional grader and a system of meat-quality grading based on the evaluation of two of five features with multiple regression analysis. Experimental results show that the system is effective.