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 a 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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    Title :

    Catfish feature identification via computer vision


    Additional title:

    Merkmalsidentifikation durch maschinelles Sehen bei Flossenfischen, speziell beim getüpfelten Zwergwels


    Contributors:
    Jia, P. (author) / Evans, M.D. (author) / Ghate, S.R. (author)

    Published in:

    Transactions of the ASAE ; 39 , 5 ; 1923-1931


    Publication date :

    1996


    Size :

    9 Seiten, 16 Bilder, 17 Quellen



    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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