Catfish feature identification via computer vision
Jia, P. | Evans, M.D. | Ghate, S.R.
Computer vision algorithms for automated channel catfish (Ictalurus punctatus) processing were developed to: (1) detect the orientation of a catfish; (2) identify the head, tail, pectoral, ventral, and dorsal fins of a catfish; and (3) determine cutting lines for deheading, detailing, and definning (dorsal and ventral fins). The algorithms are invariant to translation, rotation, and scaling of a catfish and are robust to noise. They may be applied to most fin fish processing, and are not limited to catfish Canny edge detection and a labeling and tracking algorithm were applied to locate the boundary of a catfish. A two-stage, model-based, catfish segmentation algorithm was proposed to locate each part of a catfish. A dominant point detection scheme was proposed and applied to find the points that connect each part of a catfish. Then morphological knowledge of the catfish was used to locate the feature points of each part of the catfish and to determine the cutting lines. The angle of the major axis and center of mass were used to represent the orientation of a catfish.
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