86results about "Carcasses classification/grading" patented technology

This invention generally relates to a system and process for implementing computer vision and machine learning in a poultry processing plant. In one mode of operation, the invention is configured to analyze images of processed poultry moved by a conveyor to automatically determine if the poultry carcasses have any defects. In another mode of operation, the system is configured to analyze images of processed poultry parts being weighed on a scale. In this mode of operation, the system is configured to automatically classify the poultry carcass part being weighed.

The invention discloses a live pig slaughtering whole process management method and system based on a segmentation model, and relates to the technical field of live pig slaughtering management. Fat content and skeleton parameters are obtained through zoning measurement, a prediction result of meat distribution is constructed in combination with real-time environment data, the recognition accuracy and data stability are improved, cutting precision is guaranteed through structural precision in combination with production line capacity and equipment load information, serial numbers are subjected to iterative sorting optimization through a genetic algorithm, and the cutting efficiency is improved. Production line conflicts and resource waste are reduced, the adaptability and dynamic cooperation capability of the whole processing system are enhanced, the beat matching efficiency is improved through path continuity, the cutting deviation and error propagation are reduced, the segmentation sequence is adjusted in combination with equipment load change and conveying rhythm, and data-driven closed-loop management and control from posture recognition to cutting execution stages is achieved; and the precision management, the cutting consistency and the production flow robustness of the slaughter link are effectively improved.

A method, arrangement and apparatus are provided for training at least one neural network for locating bony parts present in a poultry leg. The method includes the steps: conveying the poultry legs in a conveying direction by a conveying device; acquiring digital images of the front side or back side of each of the poultry legs conveyed past the imaging system by a first optical imaging system; sequentially providing the digital images as input data to a first neural network configured for locating the bony parts, wherein the first neural network for locating the bony parts has been trained by a described method; and determining position data of the bony parts by the first neural network; and providing the position data, for display and / or transmission, to a downstream machine for processing the poultry legs on the basis of the determined position data.

Described embodiments relate to methods of determining quality assessment measures of carcases. The method comprises determining video data comprising a sequence of frames, wherein at least some of the frames depict a part of a carcase to be quality assessed. For a first frame of the sequence of frames, the method comprises a) determining a frame suitability score for assessing a first trait; b) responsive to the frame suitability score being greater than a threshold frame suitability score for the first trait, determining the frame as a suitable frame for assessing the first trait; c) determining, by a segmentation model, a region of interest in the frame for assessing the first trait; d) determining, by a first trait prediction model, a prediction score for the first trait based on the determined region of interest; and e) determining an assessment confidence rating for the first trait. The method further comprises responsive to determining that the assessment confidence rating for the first trait has not exceeded the assessment confidence threshold for the first trait, performing steps a) to e) for a subsequent frame in the sequence; and responsive to determining that the assessment confidence rating for the first trait has exceeded the assessment confidence threshold for the first trait, determining a quality assessment measure of the first trait based on the prediction score for the first trait of the determined suitable frames.

An apparatus for facilitating ultrasound scanning of objects. The apparatus comprises a housing defining a reservoir. The housing comprises: a body comprising a transducer mounting, the transducer mounting configured to support an ultrasound transducer; a flange extending from the body to define side walls of the reservoir; and a first flexible membrane mounted on a free end of the flange, the first membrane defining an external contact surface for making contact with an object to be scanned, and the first flexible membrane configured to allow ultrasound waves to propagate therethrough. The reservoir is configured to retain ultrasound propagation fluid to facilitate ultrasound wave propagation between the transducer and the first flexible membrane.

This invention generally relates to a system and process for implementing computer vision and machine learning in a poultry processing plant. In one mode of operation, the invention is configured to analyze images of processed poultry moved by a conveyor to automatically determine if the poultry carcasses have any defects. In another mode of operation, the system is configured to analyze images of processed poultry parts being weighed on a scale. In this mode of operation, the system is configured to automatically classify the poultry carcass part being weighed.

Livestock animal assessment models may be trained using ultrasound images of livestock animals taken over their lifespan and quality measurements of the same livestock animals taken after slaughter that provide quantitate indications of meat quality and / or tenderness. Once generated and / or trained, the livestock animal assessment models may be used to predict livestock quality and / or value during lifespan using ultrasound images of animal tissue and / or other pre-slaughter measurements.

One embodiment of the present invention provides an automated slaughter robot system including a scanning module configured to scan a slaughtered animal moving while hanging on a hanger, a work determination module configured to determine whether to cut or dismember the slaughtered animal based on an image provided from the scanning module, a work control module configured to extract a required cutting or dismembering part of the slaughtered animal from the image acquired through the scanning module, and a slaughter robot module configured to cut or dismember the slaughtered animal according to a work command provided from the work control module.

A carcass processing system having a method and apparatus for monitoring the quality of processing carcasses manually or automatically (robotically) by implementing a vision-based architecture, incorporating machine learning and / or artificial intelligence (Al) and empirical data analysis forming a vision-based quality control and audit system, and method of performing the same, for the purpose of performing qualilty cutting of the carcasses, and making adjustments to the cutting apparatus during processing.

A method for processing a live fish can include: determining a set of fish attributes of a fish, optionally sorting the fish based on the set of fish attributes, euthanizing the fish, exsanguinating the fish, and / or any other suitable steps. In variants, the method can additionally or alternatively include: discarding the fish after sorting, further processing the fish, and / or tracking the fish. However, the method can additionally and / or alternatively include any other suitable elements.

The method performed by a computer conducting a quality assurance (QA) analysis of a QA sample may include: acquiring image sensor data of the QA sample using an image sensor assembly; generating at least one of a 2D model and a 3D model of the QA sample using the image sensor data with a computing device; and performing a QA analysis of the QA sample by comparing data points of at least one of the 2D model and 3D model of the QA sample with the corresponding 2D model and 3D model from the QA specification of the QA sample with the computing device.

A computer-implemented method of performing a quality assurance (QA) analysis for a QA sample may include capturing image sensor data of a QA sample with an image sensor assembly; generating, with a computing device, at least one of a 2D model and a 3D model of the QA sample using the image sensor data; and performing, with a computing device, a QA analysis of the QA sample by comparing data points of the at least one of the 2D model and 3D model of the QA sample and a corresponding 2D model and 3D model from a QA specification of the QA sample.

A method for processing a live fish can include: determining a set of fish attributes of a fish, optionally sorting the fish based on the set of fish attributes, euthanizing the fish, exsanguinating the fish, and / or any other suitable steps. In variants, the method can additionally or alternatively include: discarding the fish after sorting, further processing the fish, and / or tracking the fish. However, the method can additionally and / or alternatively include any other suitable elements.

Meat cutting tool (1) comprising a cutting tool support structure (2) and a circular cutting blade (7) connected to the cutting tool support structure (2), wherein the circular cutting blade (7) is arranged to rotate around a rotational axis (9). The tool also comprises a guide spear (3) connected to the cutting tool support structure (2) at a first longitudinal end (4) of the guide spear (3) so that the guide spear (3) is overlapping the circular cutting blade (7) as seen in the direction of the rotational axis (9), wherein the guide spear (3) is extending along a part of the periphery of the circular cutting blade (7) perpendicularly to the axis of the blade, and wherein a second longitudinal end (5) of the guide spear (3) taper off, and wherein the circular cutting blade (7) and the guide spear (3) are connected to the cutting tool support structure (2) so that the circular cutting blade (7) and the guide spear (3) are maintained in a mutually fixed position during use of the meat cutting tool (1). The meat cutting tool (1) further comprises drive means (18) arranged for rotating the circular cutting blade (7) around the rotational axis (9) so that the periphery of the circular cutting blade (7) is moving towards the first longitudinal end (4) at the guide spear (3).

The invention relates to a method for automatically determining at least one quality parameter characterizing the processing of a carcass part, comprising the following steps: conveying the carcass part as an input product in a conveying direction to a first processing machine (11) by means of a conveying device (10), a first processing machine for performing a first processing step for processing the carcass portion into an output product; acquiring input sensor data of the carcass part by means of at least one sensor device (12) prior to performing the first processing step; classifying partial data related to the machining quality of the first machining step from the input sensor data; determining the at least one quality parameter based on the partial data; and providing the at least one quality parameter for display and / or transmission to a downstream processing machine, the downstream processing machine being adapted to perform at least one subsequent processing step based on the determined quality parameter. The invention also relates to a corresponding device.

An X-ray imaging system includes an X-ray detector; a plurality of X-ray sources configured to illuminate the detector from different perspectives; a shutter in a transmission plane between each X-ray source controlling transmission of X-rays from each X-ray source to the detector; and a processor configured to receive and process X-ray data from the detector. The shutter may be configured to illuminate the detector alternately with each X-ray source. The processor may determine 3D information about an object from the processed X-ray data. Also provided are methods for processing X-ray data and different embodiments of shutters to alternately illuminate X-ray detectors.

The present invention relates to a trimming assembly comprising an adjustable arm, a cutting assembly having cutting utensil and a depth gauge, the cutting assembly connected to a distal end of the adjustable arm, and a sensing arrangement adapted to determine the fat height and meat height of at least one node of a meat material. The present invention alleviates and / or addresses some of the shortcomings of the present meat trimming apparatus or approaches.

The invention relates to a method for the automated inspection of carcasses (10) by means of ultrasound imaging, the method comprising the steps of: conveying the carcasses (10) along a conveying path (11) by means of a conveying device; and scanning the carcasses (10) by means of ultrasound using an imaging ultrasound sensor (12) in order to generate image data by bringing the carcasses (10) into lateral contact with an ultrasound contact face (13) of the imaging ultrasound sensor. The invention also relates to a corresponding apparatus. Furthermore, the invention to a method for automatically deboning poultry legs, which is characterised by: performing the automated inspection of carcasses (10) by means of ultrasound imaging using the method for the automated inspection of carcasses; locating the position of the knee joint as a skeletal component in the poultry legs by evaluating the image data; and deboning the poultry legs on the basis of the position of the knee joint. The invention also relates to a corresponding arrangement for automatically deboning poultry legs.

A method for processing a live fish can include: determining a set of fish attributes of a fish, optionally sorting the fish based on the set of fish attributes, euthanizing the fish, exsanguinating the fish, and / or any other suitable steps. In variants, the method can additionally or alternatively include: discarding the fish after sorting, further processing the fish, and / or tracking the fish. However, the method can additionally and / or alternatively include any other suitable elements.

The present invention relates to a static CT detection device, comprising: a shielding body, which forms a detection channel through which a detected object can pass; a ray source, which emits rays for detecting the detected object when the detected object passes through the detection channel; and a detector, which acquires the rays emitted by the ray source and passing through the detection channel, wherein an opening is formed on the shielding body, and the opening extends from the entrance of the detection channel to the exit of the detection channel.

The described embodiments relate to a method of determining a quality assessment metric for a carcass. The method includes determining video data comprising a sequence of frames, wherein at least some of the frames depict a portion of a carcass to be quality assessed. For a first frame of the sequence of frames, the method comprises a) determining a frame suitability score for assessing a first trait; b) in response to the frame suitability score being greater than a threshold frame suitability score for the first trait, determining the frame as a suitable frame for assessing the first trait; c) determining a region of interest for evaluating the first character in the frame through a segmentation model; d) determining a predicted score of the first character based on the determined region of interest by a first character prediction model; and e) determining a rating confidence rating for the first trait. The method further comprises: in response to determining that the rating confidence rating of the first trait has not exceeded a rating confidence threshold of the first trait, performing steps a) to e) on subsequent frames in the sequence; and in response to determining that the rating confidence rating for the first trait has exceeded the rating confidence threshold for the first trait, determining a quality rating metric for the first trait based on the determined predicted score for the first trait suitable for a frame.

The invention provides an automatic viscera separation device for synchronous quarantine of pig slaughtering, and relates to the technical field of pig slaughtering. The automatic viscera separation device for synchronous quarantine of pig slaughtering comprises a support and a programmable control box, the programmable control box is arranged at the front end of the support, a base is arranged on the upper end face of the support, a supporting seat is arranged on the upper end face of the base, and a top seat is arranged on the upper end face of the supporting seat. Annular conveying lines are arranged on the lower end face of the top seat and the upper end face of the base, a plurality of automatic clamping and separating structures are arranged on the lower end face of the annular conveying line close to the upper portion, and a plurality of automatic overturning disc structures are arranged on the upper end face of the annular conveying line close to the lower portion. The automatic turnover disc structure comprises a first substrate. The automatic tray overturning structure is arranged to bear the white viscera, when the lesion viscera appear, the lesion viscera do not need to be taken out manually, safety is improved, the white viscera do not need to be taken down manually, and the manual taking-down efficiency is reduced.

A computer-implemented method of performing a quality assurance (QA) analysis for a QA sample may include capturing image sensor data of a QA sample with an image sensor assembly; generating, with a computing device, at least one of a 2D model and a 3D model of the QA sample using the image sensor data; and performing, with a computing device, a QA analysis of the QA sample by comparing data points of the at least one of the 2D model and 3D model of the QA sample and a corresponding 2D model and 3D model from a QA specification of the QA sample.

The present invention relates to a method (100) for the analysis of carcasses (11) comprising the steps of conveying (101) the carcasses (11), detecting (102) the carcasses (11) by means of a first detection unit (14), generating (103) numerical data, processing (104) the numerical data by means of a computer unit (15), wherein characteristic attributes in a predetermined region are selected (105), or wherein the numerical data are compared (106) by means of a computer unit (15) with numerical database data contained in a database (16) in order to identify (107) characteristic attributes, providing (108) the characteristic attributes for display (109) and / or transmission (110) to at least one downstream machine (20) for assessment (111) or processing (112) of the carcasses (11) or carcass regions on the basis of the characteristic attributes determined. The invention also relates to a method (200) for training at least one neural network (17, 18), to a non-volatile computer-readable storage medium and also to a corresponding device (10) for the analysis of carcasses (11).

The present invention relates to a food processing line (10), the food processing line (10) comprising an injection device (2) configured to inject a liquid into food; at least one microwave sensor (1, 3) configured to sense microwave transmission data of the food product, the microwave sensor (1, 3) comprising a microwave transmitter (11) and a microwave receiver (12) spaced apart from the microwave transmitter (11), the microwave receiver (12) further configured to receive a transmission signal transmitted by the microwave transmitter (11); and a control unit (4) configured to receive the microwave transmission data from the microwave sensor (1, 3) and to control the injection device (2) based on the microwave transmission data received from the microwave sensor (1, 3).

An apparatus and method are described that makes possible the automatic measurements of temperature in poultry items moving on a conveyor. The apparatus is characterized in that it can receive information from sensors located upstream in the conveyor line about incoming poultry items. The apparatus can further adapt the position of temperatures probes with respect to the size and shape and speed of an item to be measured and insert one or more temperature probes into the item in such a way that the temperature probe will always be inserted at the same relative spot and at the same depth in items that have the same size or shape. After the temperature probe has been inserted, it will move with the poultry items on the conveyor line for sufficient time and distance to obtain a stable temperature reading.

A computer-implemented method of performing a quality assurance (QA) analysis for a QA sample may include capturing image sensor data of a QA sample with an image sensor assembly; generating, with a computing device, at least one of a 2D model and a 3D model of the QA sample using the image sensor data; and performing, with a computing device, a QA analysis of the QA sample by comparing data points of the at least one of the 2D model and 3D model of the QA sample and a corresponding 2D model and 3D model from a QA specification of the QA sample.

This disclosure relates to a computer-implemented method for determining a physical position of an engagement part of a leaf lard. The leaf lard is located on an inner surface of a left or right part of a pig carcass. The engagement part of the leaf lard is suitable for engagement by a leaf lard removal tool for at least partially separating the leaf lard from the pig carcass. The computer- implemented method comprises receiving, from an image system, data representing an image, preferably a 3D image, of at least part of the left or, respectively, right part of the pig carcass. The image does not comprise an image region that represents the engagement part. The method also comprises determining a reference image region in the image. The reference image region represents an anatomic characteristic feature of the pig carcass. Further, the method comprises determining, based on the determined reference image region, the physical position of the engagement part of the leaf lard.

A method for processing a live fish can include: determining a set of fish attributes of a fish, optionally sorting the fish based on the set of fish attributes, euthanizing the fish, exsanguinating the fish, and / or any other suitable steps. In variants, the method can additionally or alternatively include: discarding the fish after sorting, further processing the fish, and / or tracking the fish. However, the method can additionally and / or alternatively include any other suitable elements.