Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
MLESAC: a new robust estimator with application to estimating image geometry
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
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Current systems for automatic processing of salmon are not able to remove all bones from freshly slaughtered salmon. This is because some of the bones are attached to the flesh by tendons, and the fillet is damaged or the bones broken if the bones are pulled out. This paper describes a camera based system for determining the tendon positions in the tissue, so that the tendon can be cut with a knife and the bones removed. The location of the tendons deep in the tissue is estimated based on the position of a texture pattern on the fillet surface. Algorithms for locating this line-looking pattern, in the presence of several other similar-looking lines and significant other texture are described. The algorithm uses a model of the pattern's location to achieve precision and speed, followed by a RANSAC/MLESAC inspired line fitting procedure. Close to the neck the pattern is barely visible; this is handled through a greedy search algorithm. We achieve a precision better than 3 mm for 78% of the fish using maximum 2 seconds processing time.