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http://dx.doi.org/10.5307/JBE.2007.32.3.160

Quantization and Calibration of Color Information From Machine Vision System for Beef Color Grading  

Kim, Jung-Hee (Dept. of Biomechatronic Engineering, Faculty of Life Science & Technology, Sungkyunkwan University)
Choi, Sun (Dept. of Biomechatronic Engineering, Faculty of Life Science & Technology, Sungkyunkwan University)
Han, Na-Young (Dept. of Biomechatronic Engineering, Faculty of Life Science & Technology, Sungkyunkwan University)
Ko, Myung-Jin (Dept. of Biomechatronic Engineering, Faculty of Life Science & Technology, Sungkyunkwan University)
Cho, Sung-Ho (Dept. of Biomechatronic Engineering, Faculty of Life Science & Technology, Sungkyunkwan University)
Hwang, Heon (Dept. of Biomechatronic Engineering, Faculty of Life Science & Technology, Sungkyunkwan University)
Publication Information
Journal of Biosystems Engineering / v.32, no.3, 2007 , pp. 160-165 More about this Journal
Abstract
This study was conducted to evaluate beef using a color machine vision system. The machine vision system has an advantage to measure larger area than a colorimeter and also could measure other quality factors like distribution of fats. However, the machine vision measurement is affected by system components. To measure the beef color with the machine vision system, the effect of color balancing control was tested and calibration model was developed. Neural network for color calibration which learned reference color patches showed a high correlation with colorimeter in L*a*b* coordinates and had an adaptability at various measurement environments. The trained network showed a very high correlation with the colorimeter when measuring beef color.
Keywords
Beef color; Neural network; Beef grading; Machine vision system; Color calibration;
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