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16 December 2004 Shape analysis for an automatic oyster grading system
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Abstract
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. Banana shape and broken shell have a specific shape flaw (or difference) compared to the ones with good quality. Global shape properties such as compactness, roughness, and elongation are suitable and useful to measure the shape flaw. Image projection area or length of the major axis measured as global properties for sizing. Incorporating a machine vision system for grading, sorting and counting oysters supports reduced operating costs. 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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dah-Jye Lee, Xiaoqian Xu, Robert M. Lane, and Pengcheng Zhan "Shape analysis for an automatic oyster grading system", Proc. SPIE 5606, Two- and Three-Dimensional Vision Systems for Inspection, Control, and Metrology II, (16 December 2004); https://doi.org/10.1117/12.571783
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