11-03-2021 дата публикации
Номер: US20210068404A1
Принадлежит:
A method for evaluating () the health state of an anatomical element of an animal in a slaughtering plant provided with an image acquisition device. The evaluation method comprises the steps of: verifying the presence of the anatomical element; acquiring the image of the anatomical element; processing (S) the image of the anatomical element through Deep Learning techniques, generating a lesion image representing lesioned portions of the anatomical element, and a number of processed images, each representing a corresponding non-lesioned anatomical area of the animal; for each of the lesioned portions and for each of the non-lesioned anatomical areas, determining a corresponding quantity indicative of the probability that said lesioned portion corresponds to said non-lesioned anatomical area; determining a score indicative of the health state of the anatomical element, depending on the determined quantities. 1501011182220150. A method for evaluating () the health state of an anatomical element () of an animal in a slaughtering plant () , the slaughtering plant () being provided with an image acquisition device ( , ) arranged so as to acquire an image of an observation area () of the slaughtering plant () , the evaluation method () comprising the steps of:{'b': 2', '18', '22', '10', '20, 'verifying (S), through the image acquisition device (, ), the presence of the anatomical element () in the observation area ();'}{'b': 10', '20', '3', '18', '22', '10, 'if the presence of the anatomical element () in the observation area () is verified, acquiring (S), through the image acquisition device (, ), the image of the anatomical element ();'}{'b': 4', '34', '40', '18', '22', '10', '6', '10', '4', '5, 'processing (S), by an image processing unit (; ) operatively coupled to the image acquisition device (, ), the image of the anatomical element () through deep learning techniques, generating a lesion image (P), which represents lesioned portions of the anatomical element (), and ...
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