Application of Edge Detection and Binarization for Beef Grading
ZHANG Li;LI Yan-mei;SUN Bao-zhong;YU Qun-li
1. Institue of Animal Science, Chinese Academy of Agricultural Science, Beijing 100193, China；
2. College of Food Science and Engineering, Gansu Agriculture University, Lanzhou 730070, China；
3. College of Information Science and Technology, Gansu Agricultural University, Lanzhou 730070, China
Abstract：Automatic eigenvalue estimation of beef ribeye cross-section images through image processing lays the foundation
for automatic beef quality grading based on computer vision technique. Digital images of the carcass cross section between the
sixth and seventh ribs were subjected to feature extraction and detection of characteristic parameters (ribeye area, fat area ratio,
total muscle area ratio, average fat distribution, the roundness of ribeye area and ribeye muscle and fat colors) by edge detection
and binarization based on Visual C ++ 6.0. Our results showed that larger ribeye areas had better roundness, higher chromatic
values of muscle and fat and more uniform distribution of marbling, indicating better quality. On the contrary, lower-quality
ribeyes had smaller areas, lower roundness values and chromatic values of muscle and fat and uneven distribution of marbling.
The described design enables effective calculation of ribeye areas and characteristic parameters and consequent automatic
identification of beef quality grades and can be an alternative to routine grading methods.
2013, Vol. 27 
