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
  • A22B5/007—Non-invasive scanning of carcasses, e.g. using image recognition, tomography, X-rays, ultrasound
• • 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

Definitions

• This invention relates to methods of and apparatus for the automatic grading of carcasses 1n abattoirs, processing plants and the like. Hitherto, grading of carcasses has been performed manually and thus has been subject to variations between and within operators. The assessments made from such a manual operation are totally subjective. In the case of beef carcasses there is an additional problem of perspective, the hind portion often being several metres away from and above the grader. With the intention of eliminating operator variability, an automatic inspection system using video cameras and image analysis has been devised.
• Carcasses are graded according to officially accepted criteria, which vary from country to country. A transparent system has been devised on which it is possible to superimpose a variety of grading strategies. Examination of the total carcass as proposed in this method, gives information on specific sex, distribution and other attributes to which weighting factors (such as carcass weight and size) can be applied, if necessary, to determine an overall grade. Meat yiel r ' ' s calculated on the basis of normalised measurements, that is, ⁇ taking one or more views of the carcass and shrinking or expanding the image to a standard size and then comparing it with historic data from previous carcass measurements for which the meat yield and meat yield distribution has been deter ⁇ r ad.
• this information may be less precise than required, but as the database on which such predictions are based expands, the precision of yield predictions and the accuracy of yield distribution will steadily improve.
• This enhancement may progress either in a passive manner by updates to the database or, in an active way, by means of an intelligent, dynamic database which continually expands through analysis of its acquired data. Interpretation of the measurements has been based on an in-depth observation of carcass dressing operations. For instance, there are three ways of taking the hide off an animal - totally manual, semi automatic or fully automatic. All of these operate in slightly different ways, with the manual technique being the most variable of the three. This means that the method of hide removal will determine how much the fat and thin muscles of the belly region (around the cutanus truncli) is actually ripped off.
• European Patent Application No.0321981Al discloses a method and apparatus for determination of the conformation, fatness and other properties of individual cattle classes.
• the silhouette of a carcass or half carcass is recorded with a video camera in a special light screening chamber and a calculation of the parameters of the carcass made on the basis of an algorithm derived using a number of subjective assessments made by manual carcass graders.
• a second image may be recorded from the same viewpoint using different illumination.
• a method of grading carcasses after slaughter comprising the steps of checking for the presence of a carcass in the field of view of a camera, checking that the orientation of said carcass with respect to the camera is in accordance with a predetermined arrangement, exposing an image of the carcass from a plurality of different viewpoints , determining a plurality of dimensions of said carcass from said images and comparing said dimensions with stored values to determine the overall grading of said carcass.
• apparatus for the grading carcasses after slaughter comprising a plurality of video cameras adapted to be positioned adjacent to a slaughter line to expose an image of a carcass on said slaughter line from a plurality of different viewpoints, signal processing means to derive from said images a plurality of parameters characteristic of said carcass, storage means to store a corresponding plurality of parameters derived from prior measurement of reference carcasses, comparator means to compare said plurality of parameters with said corresponding plurality of parameters to derive a further parameter indicative of the g -de of said carcass and indicator means to provide an indication of the magnitude of said further parameter.
• Figure 1 is a lateral view of a well formed carcass
• side Figure 2 is a dorsal view of the same carcass half
• Figure 3 is the posterior/anterior view of the same carcass
• Figure 4 is a lateral view of a less well developed less well fleshed carcass
• Figure 5 the dorsal view of that same carcass
• Figure 6 is the posterior anterior view of that less well fleshed carcass
• Figures 7a and 7b are a schematic plan and side view of inspection apparatus set up in an abattoir.
• carcasses proceed along a rail R past a viewing position P.
• At the viewing position are three cameras C1,C2,C3 .
• One camera is positioned above the rail to provide a posterior/anterior view of the carcass.
• the other two are positioned laterally so that their lines of view are at 90° to one another and 45° to the rail.
• the same objective may be achieved by positioning the cameras at a 90° bend in the rail. In this case the cameras are again positioned above the rail and laterally at 90° to one another, but in this instance it is not necessary to orientate the carcass at 45° to the rail.
• a third option is to have the cameras staggered linearly. Such an arrangement would require the carcass to be rotated through 90° after leaving the lateral viewing position (C2) and before entering the dorsal viewing position (C3).
• the posterior/anterior camera (CD can be suitably positioned above the dorsal viewing position.
• the carcasses are viewed when in a (1) warm, (2) semi-warm or (3) cold state; the preferred states being (2) or (3) which occur some thirty minutes onwards after slaughter.
• Prior to that the bulk of the fat is translucent and any fat cover and distribution information must be interpreted in a completely different way because as the fat becomes cold it becomes more reflective and less absorbent to light, this providing greater accuracy on relative thickness data.
• the temperature is not usually measured because the conditions within the slaughterhouse and the cooling rooms are generally fairly well controlled. Each system will be calibrated to a defined set of environmental characteristics specific to that plant or abattoir. If conditions change radically, a new set of parameters will have to be installed.
• the sequence is predetermined by the way the views are tG be interpreted. Preferably, three views are taken, although two of these can actually be generated from the data of the other five.
• Three general views of the carcass are taken to provide basic data on overall carcass characteristics such as length, extent of minimum and maximum width, area distribution curves, etc.
• Each of the views are taken with a standard, non-interlaced high definition scan rate of l/50th second, up to 800 lines, although faster shutter speeds can be accommodated if necessary. For most applications alternate line sampling is sufficient and permits the picture information to be processed much faster.
• Three overall views provide the general carcass information.
• the information in these views is then processed by hardware, with a range of separation capabilities such as a differentiating circuit as an edge detector, or by dynamic software that shifts thresholds according to the type of carcass being viewed.
• Very thick fat exhibits a high reflectance value.
• sheep in particular there are some problems with the translucent nature of the fat.
• With normal direct lighting because at specific carcass locations there is a film of tissue, and as there is structure underneath it, although one is on top of the other, it acts on occasions like a mirror, particularly when the carcass is still warm. When it is at a particular angle it bends the light causing it to reflect along this collagenous material, giving rise to reduced contrast.
• the problem can be overcome by using diffuse or indirect light.
• the angularity, degree of curvature, length and other mathematical and geometric descriptions at a specific point or region on the carcass can be used objectively to define a shape at that point for comparison 1n the grading procedure and quantitatively to predict muscularity and thus lean meat yield.
• Image analysis may be used in conjunction with other techniques and devices such as multiple wavelength infra-red measurement to measure or predict moisture content and also to predict the chemical liquid content.
• the water content can be predicted with some accuracy; with butchered meat, however, the water status needs to be determined. Certain surface cuts of meat will lose water rapidly and interior cuts will lose water very slowly. The water content will effect the apparent lipid content. With on-line production techniques, the ability to measure fat and water content will enable accurate pre ic ions of lean content to be made. This is necessary, for example, in the manufacture of a calorie-controlled product.
• a cutting grid based on primitive measurements of length and width may be drawn and superimposed on each of the basic two-dimensional views. Since butchering methods vary from country to country, the advantage of this system is a new cutting grid can be superimposed to mirror the changes in butchery techniques.
• the video cameras are specially constructed to achieve a predetermined spectral response. This may be modified, according to the specific circumstances, by use of filters, structured lighting, or by selection of a charge-coupled image sensing device with the desired response. In some instances it is not desirable to have filters in front of the cameras because it degrades the quality of the image.
• the spectral response is chosen to increase and enhance the separation between the colour of the components of the meat, particularly the fatness.
• the meat may be different shades of red, purple or pink or the fat may be different shades of white or yellow
• selection of the green output gives the best separation for the lean meat colour in beef.
• Any one of the other RGB outputs may be used for the fat because the fat is reflecting across the whole spectral wavelength range.
• data can be taken from each of the RGB outputs and a polygonal database can be built up together with or in addition to luminance/chrominance data on the way in which the colours are changing relative to compositional variations in component materials or alterations in physical or chemical parameters during production. This is valuable for process control operations.
• the efficiency of the system is influenced by a number of parameters including the luminance of the lights, the reflectivity of each carcass, electronic drift in the cameras or the system hardware, it is necessary for the system to be dynamically self-calibrating on system startup and self-compensating during operation. Self-compensation during operation is achieved by a combination of camera auto-iris, signal auto-gain and dynamic modification to system parameters via the system software.
• the system described herein is also capable of self-diagnostics by means of which it is continually monitoring the performance of both the hardware and the software and will visually and audibly warn the operator of failures/errors and their degree of severity.
• such a system is capable of generating three-dimensional projections for individual carcasses.
• Using a process of normalisation it is thus possible to create and modify cutting pathways for robotic and automated systems from known and defined shapes present in the database based on the measurements quantified by the image analysis system.
• a similar approach can also be applied to carcass dressing procedures.
• an intelligent knowledge-based database - li ⁇ the system described above is capable of objective meat inspection and other allied tasks.
• image analysis is used to compile carcass data based on historic experience of what factors contribute to yield.
• a multiple thresholding technique enables fat distribution and content to be derived.
• Complex shape information can be stored as simple elements of spline curves. Other useful data, including carcass weight and sperlmen sex, can be used to bias the data as necessary.
• curves and shapes tolerance databases can be set up. This shape information will be a mixture of area measurement, connectivity analysis, length, widths, boundary points and edge detection. Predetermined divisions can be set for each of these measurements and a bias introduced to those measurements to enable accurate grade and precise yield information to be generated. In conjunction with other information, accurate grading and yield prediction can be made for the three major red meat species. With some modification this can be extended to poultry.
• This system also provides the basis for rapid automation of butchery and dressing techniques to be developed. The addition of artificial intelligence extends system use into areas of carcass welfare such as meat inspection.

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• Engineering & Computer Science (AREA)
• Life Sciences & Earth Sciences (AREA)
• Food Science & Technology (AREA)
• Health & Medical Sciences (AREA)
• Chemical & Material Sciences (AREA)
• Biochemistry (AREA)
• General Physics & Mathematics (AREA)
• Medicinal Chemistry (AREA)
• Physics & Mathematics (AREA)
• Analytical Chemistry (AREA)
• Computer Vision & Pattern Recognition (AREA)
• General Health & Medical Sciences (AREA)
• Biophysics (AREA)
• Immunology (AREA)
• Pathology (AREA)
• Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
• Length Measuring Devices By Optical Means (AREA)
• Tyre Moulding (AREA)
• Investigating Or Analysing Materials By Optical Means (AREA)
• Treatment Of Fiber Materials (AREA)

Applications Claiming Priority (2)

Publications (1)

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• 1990
  • 1990-06-22 GB GB909013983A patent/GB9013983D0/en active Pending
• 1991
  • 1991-06-21 IE IE215791A patent/IE912157A1/en unknown
  • 1991-06-24 GB GB9113566A patent/GB2247524B/en not_active Expired - Fee Related
  • 1991-06-24 EP EP19910912183 patent/EP0535125A1/de not_active Withdrawn
  • 1991-06-24 AU AU80528/91A patent/AU8052891A/en not_active Abandoned
  • 1991-06-24 WO PCT/GB1991/001018 patent/WO1992000523A1/en not_active Application Discontinuation
  • 1991-06-24 CA CA 2085124 patent/CA2085124A1/en not_active Abandoned

Non-Patent Citations (1)

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