An overview of the oyster industry in the U. S. with emphasis in Virginia shows oyster grading occurs at harvest, wholesale and processing markets. Currently whole oysters, also called shellstock, are graded manually by screening and sorting based on diameter or weight. The majority of oysters harvested for the processing industry are divided into three to four main grades: small, medium, large, and selects. We have developed a shape analysis method for an automatic oyster grading system. The system first detects and removes poor quality oysters such as banana shape, broken shell, and irregular shapes. Good quality oysters move further into grades of small, medium and large. The contours of the oysters are extracted for shape analysis. The savings produced from reducing labor, increasing accuracy in size, grade and count and providing real time accurate data for accounting and billing would contribute to the profit of the oysters industry.

 Collaborators:

Dr. Guangming Xiong, Beijing Institute of Technology, Beijing, China

Dr. Guang Hua Chang, Youngstown State Univresity

Mr. Robert Lane, Virginia Tech

 Graduate Students:

 Xiaoqian Xu, Lianche Li, and Pengcheng Zhan

1. G.M. Xiong, D.J. Lee, K.R. Moon, and R.M. Lane, “Shape Similarity Measure Using Turn Angle Cross-correlation for Oyster Quality Evaluation,“ Journal of Food Engineering, vol. 100/1, p. 178-186, September 2010.
2. G.H. Chang, G.J. Kerns, D.J. Lee, and G.L. Stanek, ”Calibration Experiments for a Computer Vision Oyster Volume Estimation System”, Journal of Statistics Education, vol. 17/2, 20 pages, July 2009.

3. D.J. Lee, X. Xu, R.M. Lane, and P. Zhan, “Shape Analysis for an Automatic Oyster Grading System”, SPIE Optics East, Two and Three-Dimensional Vision Systems for Inspection, Control, and Metrology II, vol. 5606-05, p. 27-36, Philadelphia, PA, USA, October 25-28, 2004.