Computer vision applied to detection of oyster hinge lines

A computer vision system was developed to automatically detect and locate the oyster hinge line, one step in shucking an oyster. The computer vision system consisted of a personal computer, a color frame grabber, a color CCD video camera with a zoom lens, two video monitors, a specially designed fixture to hold the oyster, a lighting system to illuminate the oyster, and the system software. The software consisted of a combination of commercially available programs and custom designed programs developed using Microsoft C(TM). Oysters, Crassostrea virginica, were washed and trimmed at the oyster hinge end to provide visual access to the exterior of the oyster hinge. The trimming process provided a flat-white surface that surrounded the dark hinge line. An image was collected on each of the three color channels (i.e., red, green, and blue) using the frame grabber and associated software. The software then segmented the object and determined which of the objects in the image war the oyster hinge line. The classification was done based on rectangularity, circularity, aspect ratio, and Euclidian distance. Test results showed that the image resolution was the most important variable influencing hinge detection efficiency. Whether or not the trimmed-off-flat-white surface area war dry or wet, the oyster size relative to the image size selected and the image processing methods used all influenced the hinge line locating efficiency. The best computer software and hardware combination used successfully located 97% of the oyster hinge lines tested This efficiency was achieved using camera field of view of 1.9 x 1.5 cm, a 180 x 170 pixel image window, and a dry trimmed-off oyster hinge end surface.