Determination of Meat Quality by Image Processing and Neural Network Techniques
Kazuhiko Shiranita, Kenichiro Hayashi and Akifumi Otsubo
Applied Electronics Division, Industrial Technology Center of Saga Prefecture, Japan
We study the implementation of a meat-quality grading system, using the concept of the marbling score, and 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 based on inputs given by a professional grader and a system of meat-quality grading based on the evaluation of three of five features with multiple regression analysis. Experimental results show that the system is effective.
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