DocumentCode :
1958001
Title :
Determination of meat quality by image processing and neural network techniques
Author :
Shiranita, Kazuhiko ; Hayashi, Kenichiro ; Otsubo, Akifumi ; Miyajima, Tsuneharu ; Takiyama, Ryuzo
Author_Institution :
Ind. Technol. Center of Saga Prefecture, Japan
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
989
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 three of five features with multiple regression analysis. Experimental results show that the system is effective
Keywords :
automatic optical inspection; backpropagation; computer vision; feedforward neural nets; food processing industry; quality control; statistical analysis; backpropagation; distribution density; image binarization; image processing; layer neural network; marbling score concept; meat-quality grading; multiple regression analysis; Agriculture; Density measurement; Equations; Feature extraction; Image processing; Inspection; Muscles; Neural networks; Regression analysis; Temperature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1098-7584
Print_ISBN :
0-7803-5877-5
Type :
conf
DOI :
10.1109/FUZZY.2000.839179
Filename :
839179
Link To Document :
بازگشت