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JRM Vol.12 No.4 pp. 474-479
doi: 10.20965/jrm.2000.p0474
(2000)

Paper:

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

Received:
February 9, 2000
Accepted:
April 11, 2000
Published:
August 20, 2000
Keywords:
Meat Quality, Image Processing, Neural Network, Multiple Regression Analysis, Beef Marbling Score, Grading System
Abstract

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.

Cite this article as:
Kazuhiko Shiranita, Kenichiro Hayashi, and Akifumi Otsubo, “Determination of Meat Quality by Image Processing and Neural Network Techniques,” J. Robot. Mechatron., Vol.12, No.4, pp. 474-479, 2000.
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