This disclosure concerns methods for processing and grading food articles including x-raying the food articles a first time and taking a 3D image of the food articles.

This disclosure concerns methods for processing and grading food articles including x-raying the food articles a first time and taking a 3D image of the food articles.

A method of determining a measure of gaping in a fish fillet item, involves the steps of obtaining three-dimensional profile data of a first area of the fish fillet item, obtaining optical imaging data of a second area of the fish fillet item, wherein the first area and the second area are overlapping at least within an overlap area; and determining the measure of gaping in the fish fillet item based on the three-dimensional profile data within the overlap area and the optical imaging data within the overlap area.

A method and a system provide a feedback data indicating quality of a food processing performed by an operator. The method and system involve acquiring at least one image data of a food product from an operator; and processing the acquired image data. The processing includes detecting whether undesired objects are present in the food product, obtaining, in case undesired objects are detected, position data of the undesired objects within the food product, and utilizing the position data in issuing a feedback indicator indicating a position where the detected undesired objects are present within the food product processed by the operator.

An apparatus for detecting surface characteristics on food objects conveyed by a conveyor, has a first imaging device for capturing two-dimensional image data (2D) and a second imaging device for capturing three-dimensional image data (3D) of a food object. At least one image processing unit is configured to utilize either one of the 2D or the 3D image data in determining whether a potential defect is present on the surface of the food object. In case such a potential defect property is found, the image processing unit determines a surface position of the potential defect, and utilizes the remaining one of the 2D or the 3D image data in determining whether an actual defect is present on the surface of the food object at the indicated surface position. Further, the apparatus has an output unit for outputting defect related data in case both of the 2D and the 3D image data indicate that an actual defect is present on the surface of the food object at the indicated surface position.

A first conveyor for conveying foodstuff, a second conveyor separated from the first conveyor by a gap of free space, a top camera positioned above the gap and above the first conveyor and the second conveyor, a bottom camera positioned below the gap and below the first conveyor and the second conveyor, wherein the top camera and the bottom camera capture images of the foodstuff in the gap between the first conveyor and the second conveyor for analysis.

Disclosed is a conveyor system including a first conveyor leading to an inspection point, the first conveyor including a diversion mechanism configured to divert an object based on failing to meet an inspection parameter. The system includes a second conveyor configured to transport a container configured to receive the object from the diversion mechanism. A control module is configured to co-register an image of the object captured at the inspection point with container ID data of the container.

A method for evaluating (50) 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 (S4) 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.

An apparatus for trussing a slaughtered bird, is described the apparatus including: two or more members having trussing band retaining members, wherein the apparatus is configured to truss a slaughtered bird with a trussing band. Also described is a slaughtered bird holder, a method for trussing's a slaughtered bird, a vision system and a controller.

Meat products can be classified based on image data. Training image data is received that includes image data about first meat products. Labels associated with the first meat products are received, where each of the labels includes a type of one of the first meat products. A trained classification model is developed based on the training image data and the received labels. Image data representative of a second meat product is received. The image data is inputted into the trained classification model, where the trained classification model is configured to classify a type of the second meat product based on the image data. The type of the second meat product is received from the trained classification model.