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


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

February 9, 2000
April 11, 2000
August 20, 2000
Meat Quality, Image Processing, Neural Network, Multiple Regression Analysis, Beef Marbling Score, Grading System
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:
K. Shiranita, K. Hayashi, and A. Otsubo, “Determination of Meat Quality by Image Processing and Neural Network Techniques,” J. Robot. Mechatron., Vol.12 No.4, pp. 474-479, 2000.
Data files:

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jul. 19, 2024