WO2003034059A1 - Appareil et procede d'analyse de morceaux de viande - Google Patents
Appareil et procede d'analyse de morceaux de viande Download PDFInfo
- Publication number
- WO2003034059A1 WO2003034059A1 PCT/NZ2002/000221 NZ0200221W WO03034059A1 WO 2003034059 A1 WO2003034059 A1 WO 2003034059A1 NZ 0200221 W NZ0200221 W NZ 0200221W WO 03034059 A1 WO03034059 A1 WO 03034059A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- meat
- cut
- ofthe
- packaging
- cuts
- Prior art date
Links
- 235000013372 meat Nutrition 0.000 title claims abstract description 156
- 238000000034 method Methods 0.000 title claims abstract description 41
- 230000008569 process Effects 0.000 title abstract description 17
- 238000004806 packaging method and process Methods 0.000 claims abstract description 57
- 230000001419 dependent effect Effects 0.000 claims abstract description 18
- 238000012858 packaging process Methods 0.000 claims description 6
- 238000004891 communication Methods 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 claims description 2
- 230000004044 response Effects 0.000 claims description 2
- 239000000047 product Substances 0.000 description 97
- 238000005259 measurement Methods 0.000 description 14
- 238000003384 imaging method Methods 0.000 description 9
- 238000004513 sizing Methods 0.000 description 9
- 238000011156 evaluation Methods 0.000 description 4
- 230000004888 barrier function Effects 0.000 description 3
- 239000010868 animal carcass Substances 0.000 description 2
- 239000006227 byproduct Substances 0.000 description 2
- 230000003466 anti-cipated effect Effects 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A22—BUTCHERING; MEAT TREATMENT; PROCESSING POULTRY OR FISH
- A22B—SLAUGHTERING
- A22B5/00—Accessories for use during or after slaughtering
- A22B5/0064—Accessories for use during or after slaughtering for classifying or grading carcasses; for measuring back fat
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/04—Sorting according to size
- B07C5/12—Sorting according to size characterised by the application to particular articles, not otherwise provided for
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
- B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/02—Food
- G01N33/12—Meat; Fish
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
- G06T7/521—Depth or shape recovery from laser ranging, e.g. using interferometry; from the projection of structured light
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30128—Food products
Definitions
- the present invention relates to an apparatus and process for analyzing cuts of meat.
- a conveyor is generally used to transfer each ofthe various classes of meat cuts to the bagging workstation. It is desirable to package each ofthe cuts of meat in bags having proper characteristics for packaging the cut of meat. For example, it may be desirable to package a cut of meat in a bag having information regarding the cut of meat printed on the bag. Additionally, it may be desirable to package a cut of meat in a bag having physical characteristics such as barrier, non-barrier, or bone guard qualities. In the past, there has not been an apparatus or process for identifying the product class of each ofthe cuts of meat and transmitting the product class information to the bag making device for producing a bag having the proper characteristics for packaging the cut of meat. Any discussion of the prior art throughout the specification should in no way be considered as an admission that such prior art is widely known or forms part of common general knowledge in the field.
- Cut of meat means a portion of an animal carcass that has been separated from the animal carcass.
- Product class means a particular type of cut of meat. Examples include, without limitation sirloin, tenderloin, brisket and other cuts as will be appreciated by those skilled in the relevant arts, including any customized cuts that may be made not conforming to a standard cut. Summary of the Invention
- a method of analyzing cuts of meat including: storing information defining a plurality of possible product classes as predetermined values of a set of attributes; detecting attributes of a cut of meat to be analyzed, the detected attributes corresponding to attributes in said set of attributes; for each said possible product class comparing each detected attribute with its corresponding attribute in said set of attributes and dependent on the comparison computing a total score indicating the likelihood ofthe cut of meat being a member of that possible product class; identifying the product class ofthe cut of meat as the possible product class having the total score indicating the most likelihood ofthe cut of meat being a member of that possible product class.
- said set of attributes includes values for cut weight and specific cut dimensions.
- said set of attributes includes values for at least one of cut volume and cut cross-section.
- said set of attributes includes values for the symmetry ofthe cut of meat over at least one of a longitudinal and lateral axis.
- said set of attributes includes values for at least one ofthe cut height variation and cut area variation.
- said total score is computed as a weighted sum ofthe result for each attribute ofthe step of comparing each detected attribute with its corresponding attribute in said set of attributes, wherein a weighting for each said result is specific for each product class and is predetermined based on the extent that that the particular attribute distinguishes that product class from others of said possible product classes.
- a method of packaging cuts of meat in a processing line including a supply of cuts of meat of different classes, the method including receiving cuts of meat from said supply, analyzing each cut of meat in accordance with the method of any one ofthe preceding claims to determine the product class ofthe cut of meat under analysis and varying a packaging process for the cut of meat dependent on the determined product class.
- the step of varying a packaging process for the cut of meat dependent on the determined product class includes selecting a type of packaging for the cut of meat dependent on the determined product class.
- the method includes printing indicia onto packaging for a cut of meat or onto a label for said packaging, wherein the step of varying a packaging process for said cut of meat dependent on the determined product class includes printing different indicia on the packaging dependent on the determined product class.
- the method further includes printing with said indicia further indicia that specifies particular quality or grade characteristics ofthe cut of meat.
- apparatus for analyzing cuts of meat including: detector means for detecting one or more product attributes of a cut of meat; machine readable information storage means containing information defining a plurality of possible product classes as predetermined values of a set of attributes; and a processor in communication with said detector means and said storage means, the processor operable to: for each possible product class retrieve from said storage means the value of each attribute in said set of attributes and compare it with the value of a corresponding attribute detected by said detector means and compute a total score indicating the likelihood ofthe cut of meat belongs to that possible product class dependent on the comparison; and provide an output indicating the possible product class that has the most likelihood that the cut of meat belongs to it.
- a packaging line for cuts of meat from a supply of variable cut classes including apparatus for analyzing cuts of meat in accordance with claim 11, a packaging workstation the operation of which is at least partially controlled by a controller, and transport means for transporting cuts of meat from said supply to said packaging workstation via said apparatus for analyzing cuts of meat, wherein said controller is operable to receive an output from said apparatus for analyzing cuts of meat identifying the product class for a cut of meat and automatically update the operation of said packaging workstation for said cut of meat in response to a change in said output between cuts of meat.
- the controller updates the operation ofthe packaging workstation by changing the type of packaging supplied for said cut of meat.
- the packaging workstation further includes a printer for printing indicia onto packaging for said cut of meat or onto a label for said packaging, wherein the controller updates the operation ofthe packaging workstation by causing the workstation to print different indicia on the packaging or label.
- said controller further controls the printer to print further indicia on said packaging or said label, the further indicia that specifying particular quality or grade characteristics ofthe cut of meat as determined by said processing means dependent on attributes detected by said detecting means.
- said controller is the same device as the processor of said apparatus for analyzing cuts of meat.
- FIG. 1 is a meat packaging system including an identification device ofthe present invention.
- FIG. 2 is a flow chart ofthe product evaluation sequence for identifying the product class of each cut of meat.
- FIG. 3 is an example of an array used as part of the product evaluation sequence ofthe present invention.
- FIG. 4 is an example of indicia that may be printed onto packaging.
- the present invention relates to an apparatus and process for identifying the probable product class of cuts of meat by comparing measured properties of each ofthe cuts of meat to reference values for the properties of each ofthe product classes.
- the invention may provide improved distribution and handling ofthe cuts of meat after they have been packaged by the application of identifying indicia onto the packages for the meat.
- FIG. 1 illustrates a meat packaging system 10 where cuts of meat are transferred along a conveyor 11, in this embodiment represented by a series of conveyors 12, through a cut-sizing device 14 to a bagging workstation 16.
- the bagging workstation 16 may include one or more bag making devices, in this embodiment four bag making devices 18a-18d such as the devices disclosed in either or both of published New Zealand Patent Applications 263,260 and 239,153, which are incorporated herein by reference in their entirety.
- the bagging workstation 16 may also include a loading apparatus 17 for assisting in the loading of cuts of meat into bags.
- the loading apparatus.17 may be the apparatus described in International Patent Publication No. WO 02/076832, which is hereby incorporated herein in its entirety.
- the bag making devices 18a-d may be controlled by a processor 15 as described in International Patent Publication No. WO 01/88930, which is also hereby incorporated herein by reference in its entirety.
- the bagging workstation 16 may alternatively include any other bag making device, or any number of bag making devices, apparent to one skilled in the art.
- An appropriate communication channel 19 is provided between the processor 15 and bag making devices 18a-d.
- the processor 15 need not be a single device and may for example include multiple microprocessors or microcontrollers in communication with each other.
- the processor 15 includes an associated memory 21, which contains the instructions to control the operation of the processor 15 and information defining the product classes for comparison with the measurement data received from the cut-sizing device 14.
- Each bag making device 18a-d includes a printer 20 for applying indicia to the bags.
- the printers 20 may be controlled by the processor 15, either directly or through a local controller (not shown) for each bag making device 18a-d or group of bag making devices 18.
- the printers 20 may thermally print indicia onto plastic tubing used to make the bags.
- the cut-sizing device 14 may include a three dimensional (3D) imaging assembly
- the 3D imaging assembly determines the length ofthe cuts of meat as well as the height and width ofthe cuts of meat at various positions along the length ofthe cuts of meat.
- the 3D imaging assembly may include a 670nm laser configured vertically and a sensor such as the sensor sold by Cam Sensor under the trademark CS3, mounted at 50 degrees to the horizontal to receive the reflected light.
- the 3D imaging assembly may also include photocells in a substantially horizontal plane and photocells in a substantially vertical plane.
- the 3D imaging assembly may include any 3D profiling devices apparent to one skilled in the art.
- the cut-sizing device 14 communicates with the processor 15, which receives the measurements from the 3D imaging assembly through communication channel 17 and identifies the product class of each ofthe cuts of meat.
- the processor 15 then communicates the result of this identification process to the bagging devices 18a-d as described in more detail herein below.
- the processor 15 may be a programmable logic controller (PLC), a personal computer based controller (PC), a processor internal to the laser assembly or camera assembly, or any other processor apparent to one skilled in the art.
- the processor may be a processor for controlling the bagging workstation 16 as described above, or the processor may be coupled to the processor associated with the bagging workstation 16.
- the processor 15 may use triangulation to construct a 3D array of points to represent the dimensions of each ofthe cuts of meat or the processor 15 may determine the dimensions ofthe cuts of meat in any manner apparent to one skilled in the art. Accordingly, the cut-sizing device 14 may be the device disclosed in International Patent Publication No. WO 01/88930.
- FIG. 2 illustrates an embodiment of a product evaluation sequence, generally referenced by arrow 20, that the processor 15 uses to identify the product class of each of the cuts of meat.
- the 3D imaging assembly analyses the cut of meat and transmits the cut of meat's attributes to the processor 15, see step 22.
- the processor uses data acquired by the 3D imaging assembly to determine various attributes ofthe cut of meat, including cut length, cut width, and cut height.
- the processor can determine additional cut attributes such as: cut volume, maximum cross sectional area, maximum cut height, average cut height, cut height variation, cut area variation, longitudinal symmetry, lateral symmetry, width/length ratio. Other attributes can be determined and used to classify the cuts as well.
- Cut height variation may be defined as the absolute difference between the height ofthe cut one-quarter ofthe length in from the front ofthe cut, and the height ofthe cut one-quarter ofthe length in from the back ofthe cut.
- Cut area variation may be defined as the absolute difference between the cross sectional area ofthe cut one-quarter ofthe length in from the front ofthe cut, and the cross sectional area ofthe cut one-quarter ofthe length in from the back ofthe cut.
- the longitudinal symmetry may be defined as the sum ofthe differences of height at various equi-distances away from the center ofthe cut measured in the longitudinal direction.
- the lateral symmetry may be defined as the sum ofthe differences of height at various equi-distances away from the center ofthe cut measured in the lateral direction. It is important to note that the measurements listed provide the same or similar results whether the cut of meat is loaded forward or backwards on the conveyor 12. Depending on the specific product attribute, the measured values may be averaged or otherwise evaluated to determine from multiple measurements a single value that can be used.
- a number of measurements at spaced intervals across the cut of meat may be taken, with the average, maximum or 75 percentile for example being used as a single measurement for the product width.
- the processor 15 is then loaded with the first reference statistical values associated with each ofthe possible product classes in step 24.
- the statistical values are stored in memory 21 and may include the average and standard deviation, the average and range, or any other relevant statistical information as would be apparent to one skilled in the art of each ofthe attributes ofthe cuts of meat for each ofthe possible product classes.
- the statistical values may be based on previous measurements of various cuts in each ofthe possible product classes by the cut-sizing device 14. Alternatively, the statistical values may be determined in any other manner apparent to one skilled in the art.
- the statistical values may be loaded into the processor prior to the initiation ofthe product evaluation sequence 20.
- the processor 15 compares the first attribute ofthe cut of meat to the statistical values for the first attribute ofthe first possible product class in step 26.
- the comparison between the first attribute ofthe cut of meat and the statistical values for the first attribute ofthe first possible product class is assigned a statistical score.
- the score is based on the likelihood ofthe cut of meat being a member ofthe first possible product class. For example, the comparison ofthe cut of meat's length with the statistical values for the length ofthe first possible product class may receive a score between zero and one hundred.
- a score of zero may indicate a very unlikely match and a score of one hundred may indicate a very likely match.
- the score may then be multiplied by a weighting factor to adjust for the significance ofthe cut of meat's length in determining the possible product class.
- the weighting factor may be different for the same attribute in different possible product classes depending on the extent to which the particular attribute differentiates the product class from the other possible product classes. For example, if cuts in one product class are known to be significantly longer than the cuts in most or all ofthe other product classes, then the length attribute may be more heavily weighted. Similarly, if cuts of one product class have a similar length to other cuts of product classes, then the length attribute will be lightly weighted, or even given a zero weighting.
- the set of product attributes used may include only one attribute, although using multiple attributes is anticipated to increase the accuracy of the system in most cases.
- the processor 15 determines a total theoretical score, or in other words the score that would result if the cut was a perfect match to the reference cut for the particular cut attribute in step 28.
- the score and theoretical score are then stored in an array 44 in the memory 21.
- An example of an embodiment ofthe array 44 is shown in FIG. 3. The embodiment shown in FIG. 3 is described in greater detail below.
- the processor 15 may determine whether all ofthe attributes ofthe cut of meat have been compared to the statistical values for the attributes ofthe first possible product class and assigned a score in step 32. If all ofthe attributes ofthe cut of meat have been compared, the processor may continue on to step 34 as described below. However, if there are additional attributes ofthe first possible product class that have not been compared and assigned scores, the processor may return to step 26, loading the second product attribute as indicated by step 30, to compare the second attribute ofthe cut of meat to the statistical values for the second attribute ofthe first possible product class. The processor 15 may then compare the second attribute ofthe cut of meat to the statistical values for the second attribute ofthe first possible product class and assign a corresponding score and store the total theoretical store in steps 26 and 28 respectively.
- the processor again determines whether all ofthe attributes ofthe cut of meat have been compared to the attributes ofthe first possible product class and assigned a score in step 32. Accordingly, the remaining attributes ofthe cut of meat are compared to the remaining statistical values for the attributes ofthe first possible product class and assigned scores via step 26. This process continues until a score has been assigned for the comparison of each ofthe attributes ofthe cut of meat to each ofthe statistical values for the attributes ofthe first possible product class.
- the processor assigns a confidence score for the first possible product class via step 34.
- the confidence score may be calculated by dividing the sum ofthe scores for the comparison of each attribute ofthe cut of meat to each possible product class by the sum ofthe theoretical scores for the comparison of each cut of meat to each ofthe possible product classes. A higher confidence score may indicate a higher likelihood a cut of meat is ofthe possible product class for which the confidence score is assigned. Alternatively, the confidence score may be assigned in any manner apparent to one skilled in the art.
- the processor 15 determines whether all ofthe possible product classes have been assigned a confidence score via step 38. If every possible product class has been assigned a confidence score, the processor continues on to step 40 as described below. However, if the processor 15 determines there is a possible product class that has not been assigned a confidence score the processor returns to step 26 to compare the first attribute ofthe cut of meat to the statistical values for the first attribute ofthe possible product class that has not been assigned a confidence score via step 26. As described above, the processor then compares each ofthe attributes ofthe cut of meat to the statistical values for the attributes ofthe possible product class and assigns scores for each ofthe comparisons via step 26, and assigns a confidence score for the possible product class via step 34.
- the processor determines the likely product class ofthe cut of meat via step 40.
- the likely product class ofthe cut of meat may be determined by selecting the possible product class with the highest confidence score.
- the processor 15 may transmit the likely product class information as well as the information regarding the measured and calculated attributes ofthe cut of meat to the bag making device, printer, or other machine in the line having a controller.
- the bag making device 18 may then use the information transmitted by the processor 15 to: select an appropriate feed of tube stock to make a bag for packaging the cut of meat; print a label containing a product code, a description, or a logo on the bag for packaging the cut of meat; make an appropriately sized bag for packaging the cut of meat; or any other activity apparent to one skilled in the art.
- selecting an appropriate feed of tube stock to make a bag for packaging the cut of meat may include selecting a feed of tube stock having appropriate barrier qualities, appropriate width, appropriate markings, or any other attribute apparent to one skilled in the art.
- the printers 20 may apply the selected information directly onto the tubing that forms the bags made by the bag making apparatus 18a-d.
- the information printed onto a bag or onto label may include a group code and one or more product codes.
- a portion of a bag 41 a group code, for example Tl may indicate the class ofthe product, for example a tenderloin.
- the product codes, in the example in Figure 4 Wl and FI may indicate selected measured attributes or characteristics determined from measured attributes. Wl may indicate a weight range that the cut falls within, the weight measured by suitable scales 100 (see Figure 1).
- FI may be an indication ofthe cut quality, dependent on the particular shape ofthe cut. For example, if the reference possible product classes represent the ideal shape, FI may indicate a high quality cut having a confidence score in the range of 80 to 100%.
- the printers 20 may alternatively be located downstream in the processing line of the packaging apparatus 18, in which case the processor 15 may include two parts, one concerned with control ofthe packaging apparatus 18 and another concerned with the control ofthe printers 20.
- a measurement ofthe cut weight may be used in combination with the other product attributes measured by the cut-sizing device 14 to establish the product class, the weight measurement treated in the same way as the measurements of other attributes, being assigned a weighting factor to indicate it relative importance to the other attributes and incorporated into the confidence score.
- the normalized value the conversion ofthe Z value into a probability using the normal distribution, is stored in a normalized value column 52.
- the score is attained by multiplying the normalized value by 100 and is stored in a score column 54.
- the adjusted points are determined by multiplying the score and the weighting factor and are stored in a cut points column 56.
- the weighting factor is the value labeled points that is stored in the statistical data column 46.
- the total possible points for each property, or attribute is stored in a total possible points column 58.
- a totals section 60 includes the sum of all the values stored in the cut points column 56, the sum of all the values stored in the total possible points column 58, and the confidence score, or cut score.
- the confidence score, or cut score is the sum ofthe values in the cut points column 56 divided by the sum ofthe values in the total possible points column 58, shown as a percentage.
- the confidence score for each possible product class is compared to other confidence scores for the remaining product classes to determine ofthe possible product classes, which is the most likely product class for each cut of meat. As discussed herein above, the possible product class with the highest confidence score may be selected as the product class and this information communicated to processor 15 so that an appropriate code may be printed onto the bag produced for the particular cut of meat by one ofthe printers 20.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Food Science & Technology (AREA)
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Biophysics (AREA)
- Optics & Photonics (AREA)
- Geometry (AREA)
- Medicinal Chemistry (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Quality & Reliability (AREA)
- Meat, Egg Or Seafood Products (AREA)
Abstract
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
NZ51494101 | 2001-10-18 | ||
NZ514941 | 2001-10-18 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2003034059A1 true WO2003034059A1 (fr) | 2003-04-24 |
Family
ID=19928794
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/NZ2002/000221 WO2003034059A1 (fr) | 2001-10-18 | 2002-10-18 | Appareil et procede d'analyse de morceaux de viande |
Country Status (1)
Country | Link |
---|---|
WO (1) | WO2003034059A1 (fr) |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102006032423A1 (de) * | 2006-07-13 | 2008-01-17 | Delipetkos, Elias, Dipl.-Inform. (FH) | Verfahren und Vorrichtung zur Bestimmung des Fettgehaltes einer Gesamtheit von Fleischstücken |
WO2009087258A1 (fr) * | 2008-01-10 | 2009-07-16 | Universidad De Santiago De Chile | Dispositif portable et procédé de détermination de la qualité d'un morceau de viande |
US11120540B2 (en) | 2018-08-16 | 2021-09-14 | Thai Union Group Public Company Limited | Multi-view imaging system and methods for non-invasive inspection in food processing |
US11497221B2 (en) | 2019-07-19 | 2022-11-15 | Walmart Apollo, Llc | Systems and methods for managing meat cut quality |
Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO1992000523A1 (fr) * | 1990-06-22 | 1992-01-09 | British Technology Group Ltd | Procede et appareil de classification automatique de carcasses |
GB2285126A (en) * | 1993-12-07 | 1995-06-28 | Paul Bernard David Newman | Grading and quality control of meat cuts |
WO1995021375A1 (fr) * | 1994-02-01 | 1995-08-10 | Tulip International A/S | Systeme, appareil et procede de determination en direct des caracteristiques qualitatives de morceaux de viande, et dispositif d'eclairage de morceaux de viande |
US5668634A (en) * | 1992-07-03 | 1997-09-16 | Newman; Paul Bernard David | Quality control and grading system for meat |
WO1997041533A1 (fr) * | 1996-04-25 | 1997-11-06 | Knud Thomsen | Procede d'apprentissage destine a un systeme d'analyse d'images servant a analyser un objet, et utilisations de ce procede |
WO1998008088A1 (fr) * | 1996-08-23 | 1998-02-26 | Her Majesty The Queen In Right Of Canada, As Represented By The Department Of Agriculture And Agri-Food Canada | Procede et dispositif pour utiliser l'analyse d'image afin de determiner les caracteristiques d'une viande ou d'une carcasse |
US5793879A (en) * | 1992-04-13 | 1998-08-11 | Meat Research Corporation | Image analysis for meat |
WO2000049400A1 (fr) * | 1999-02-18 | 2000-08-24 | Colorado State University Research Foundation | Systeme d'imagerie de viande permettant d'en prevoir l'appetibilite et le rendement |
WO2001004607A1 (fr) * | 1999-07-09 | 2001-01-18 | Rms Research Management Systems Inc. | Analyse des donnees d'images d'objets |
US6198834B1 (en) * | 1998-02-20 | 2001-03-06 | Keith E. Belk | Meat imaging system for palatability yield prediction |
WO2002016210A1 (fr) * | 2000-08-22 | 2002-02-28 | Sealed Air (Nz) Limited | Dispositif et procede destines a l'emballage de coupes de viande |
-
2002
- 2002-10-18 WO PCT/NZ2002/000221 patent/WO2003034059A1/fr not_active Application Discontinuation
Patent Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO1992000523A1 (fr) * | 1990-06-22 | 1992-01-09 | British Technology Group Ltd | Procede et appareil de classification automatique de carcasses |
US5793879A (en) * | 1992-04-13 | 1998-08-11 | Meat Research Corporation | Image analysis for meat |
US5668634A (en) * | 1992-07-03 | 1997-09-16 | Newman; Paul Bernard David | Quality control and grading system for meat |
GB2285126A (en) * | 1993-12-07 | 1995-06-28 | Paul Bernard David Newman | Grading and quality control of meat cuts |
WO1995021375A1 (fr) * | 1994-02-01 | 1995-08-10 | Tulip International A/S | Systeme, appareil et procede de determination en direct des caracteristiques qualitatives de morceaux de viande, et dispositif d'eclairage de morceaux de viande |
WO1997041533A1 (fr) * | 1996-04-25 | 1997-11-06 | Knud Thomsen | Procede d'apprentissage destine a un systeme d'analyse d'images servant a analyser un objet, et utilisations de ce procede |
WO1998008088A1 (fr) * | 1996-08-23 | 1998-02-26 | Her Majesty The Queen In Right Of Canada, As Represented By The Department Of Agriculture And Agri-Food Canada | Procede et dispositif pour utiliser l'analyse d'image afin de determiner les caracteristiques d'une viande ou d'une carcasse |
US6198834B1 (en) * | 1998-02-20 | 2001-03-06 | Keith E. Belk | Meat imaging system for palatability yield prediction |
WO2000049400A1 (fr) * | 1999-02-18 | 2000-08-24 | Colorado State University Research Foundation | Systeme d'imagerie de viande permettant d'en prevoir l'appetibilite et le rendement |
WO2001004607A1 (fr) * | 1999-07-09 | 2001-01-18 | Rms Research Management Systems Inc. | Analyse des donnees d'images d'objets |
WO2002016210A1 (fr) * | 2000-08-22 | 2002-02-28 | Sealed Air (Nz) Limited | Dispositif et procede destines a l'emballage de coupes de viande |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102006032423A1 (de) * | 2006-07-13 | 2008-01-17 | Delipetkos, Elias, Dipl.-Inform. (FH) | Verfahren und Vorrichtung zur Bestimmung des Fettgehaltes einer Gesamtheit von Fleischstücken |
DE102006032423B4 (de) * | 2006-07-13 | 2008-04-24 | Delipetkos, Elias, Dipl.-Inform. (FH) | Verfahren und Vorrichtung zur Bestimmung des Fettgehaltes einer Gesamtheit von Fleischstücken |
WO2009087258A1 (fr) * | 2008-01-10 | 2009-07-16 | Universidad De Santiago De Chile | Dispositif portable et procédé de détermination de la qualité d'un morceau de viande |
US11120540B2 (en) | 2018-08-16 | 2021-09-14 | Thai Union Group Public Company Limited | Multi-view imaging system and methods for non-invasive inspection in food processing |
US11497221B2 (en) | 2019-07-19 | 2022-11-15 | Walmart Apollo, Llc | Systems and methods for managing meat cut quality |
US11864562B2 (en) | 2019-07-19 | 2024-01-09 | Walmart Apollo, Llc | Systems and methods for managing meat cut quality |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
KR101548031B1 (ko) | 아이템 생산 제어 방법 및 시스템 | |
RU2589387C2 (ru) | Кассовый терминал | |
CA2601375C (fr) | Procede et appareil pour selection d'objets multi-destination au moyen de motes | |
KR101858404B1 (ko) | 식품 모니터링 방법 및 식품 이력 정보 위변조 방지 방법 | |
US8433437B1 (en) | Method and apparatus for sensing correct item placement for multi-destination picking | |
US20030054749A1 (en) | Apparatus and process for meat packing | |
KR101858403B1 (ko) | 식품 통합물류 시스템 | |
EP1218244B1 (fr) | Formation de lots d'objets | |
ES2368145T3 (es) | Un método y sistema para realizar el seguimiento de artículos alimentarios. | |
RU2601059C2 (ru) | Способ и устройство для контроля машины для переработки мяса | |
US10981688B2 (en) | Weight marking monitoring for packages | |
KR20190123926A (ko) | 식품 모니터링 방법 및 식품 이력 정보 위변조 방지 방법 | |
DK178364B1 (da) | Indretning og fremgangsmåde til automatisk overvågning af indretning til forarbejdning af kødprodukter | |
WO2003034059A1 (fr) | Appareil et procede d'analyse de morceaux de viande | |
EP2277020B1 (fr) | Procédé et système de traitement d'articles | |
JP2022088474A (ja) | 測定システム | |
DE60313293T2 (de) | Batch-verfahren mit rückmeldekorrektur | |
US20160165906A1 (en) | Line without checkweigher between slicing and packaging machine | |
CN116157816A (zh) | 用于检测负荷载体中的货物数量的***和方法 | |
US4372099A (en) | Method of packing poultry | |
AU2008300590A1 (en) | Method and device for transporting and handling a plurality of articles | |
DK3139753T3 (en) | Visual tracking device and method | |
WO2005008192A1 (fr) | Procede et systeme pour constituer des lots d'articles dans des receptacles | |
US6704614B1 (en) | Verification system for value added indicia applicators | |
JP4177482B2 (ja) | 物品処理システム |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A1 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BY BZ CA CH CN CO CR CU CZ DE DM DZ EC EE ES FI GB GD GE GH HR HU ID IL IN IS JP KE KG KP KR LC LK LR LS LT LU LV MA MD MG MN MW MX MZ NO NZ OM PH PL PT RU SD SE SG SI SK SL TJ TM TN TR TZ UA UG US UZ VC VN YU ZA ZM |
|
AL | Designated countries for regional patents |
Kind code of ref document: A1 Designated state(s): GH GM KE LS MW MZ SD SL SZ UG ZM ZW AM AZ BY KG KZ RU TJ TM AT BE BG CH CY CZ DK EE ES FI FR GB GR IE IT LU MC PT SE SK TR BF BJ CF CG CI GA GN GQ GW ML MR NE SN TD TG |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
DFPE | Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101) | ||
122 | Ep: pct application non-entry in european phase | ||
NENP | Non-entry into the national phase |
Ref country code: JP |
|
WWW | Wipo information: withdrawn in national office |
Country of ref document: JP |