Abstract
A program to process oyster hinge-end images and extract object features was developed using the IBM PC. A two-level minimum distance classifier was trained and applied to recognize an oyster hinge line using the extracted features. The average error rate was 3.2% of the 513 oyster samples classified. Results will be used in an automated oyster shucking system.
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