Abstract
The grades of table meat in Japan are authorized by Japan Meat Grading Association. The carcasses are inspected from two points of view such as a yield of meat and meat quality, and are graded by visual inspection of experts, so called grader. It has been difficult that we build a automatic system grading the carcasses (beef) by image processing techniques instead of grader's visual inspection, because beef grading depends on human sense of the graders.
In this paper, the authors propose new techniques such as a fuzzy shading correction, fuzzy separation of color image data, and hybrid neural network as a tool of image processing. Using the image processing with the new techniques, we construct a system which automatically grades the carcasses in accordance with the standard of Japan Meat Grading Association.
