Multispectral Imaging of Food Quality with VideometerLab3
0 likes1,151 views
The document discusses the capabilities of the VideometerLab 3 for multispectral imaging in food quality analysis, which surpasses traditional RGB imaging by utilizing 19 wavelength bands to distinguish chemical properties and detect spoilage. It highlights various applications including seafood sorting, quality control, and analyzing meat and fruit, providing both qualitative and quantitative data. The system allows rapid, non-destructive analysis with objective measurements and features advanced image processing tools for automated evaluation.
Multispectral Imaging of Food Quality with VideometerLab3
- 1. © analytikLtd analytikLtd Multispectral Imaging of Food Quality Rapid Non-destructive Surface Analysis Adrian Waltho, Analytik Ltd (Cambridge, UK) adrian.waltho@analytik.co.uk www.analytik.co.uk/multispectral-imaging • Light reflectance at separate colours • Statistical image processing • Chemical, physical and spatial properties • Differentiate | Quantify | Report
- 2. © analytikLtd Traditional colour imaging uses three broad bands of colour: Red, Green and Blue Normal Colour Imaging
- 3. © analytikLtd Normal Colour Imaging • RGB photographs have limited spectral resolution • Chlorophyll a and b give almost the same RGB signal and are not spectrally separated Chloro-a High Low High Chloro-b High Low High
- 4. © analytikLtd Multispectral Imaging Chloro-a High Low Low High Chloro-b Med High Med Low • Using just 4 wavelength bands with tightly defined ranges, Chlorophyll a and b can easily be distinguished • VideometerLab 3 uses 19 wavelength bands
- 5. © analytikLtd Multispectral Imaging • Many images obtained at selective wavelength bands • Each image pixel contains spectral data points • Spectral signature reveals chemo-specific information • See spatial location of surface chemical variation Ultraviolet Near-Infrared Infra-Red Red Yellow Green Blue Ultra-Violet
- 6. © analytikLtd VideometerLab 3 Schematic • Narrowband illumination by 19 LEDs at points between 375nm- 970nm (UV-Vis-VNIR), strobing sequentially with precise time control for known light output • Integrating sphere diffuses light onto sample from all angles • 5 mega-pixel monochrome CCD camera captures % reflectance at each LED wavelength for each image pixel, NIST calibration • Optional Emission filter wheel for fluorescence detection and Bright-field or Dark-field back lighting Camera LEDs Integrating sphere Emission filter wheel Sample
- 7. © analytikLtd VideometerLab 3 Schematic • Precise control at each separate point of the 375-970nm spectrum, only possible with LEDs, allows optimal illumination for best signal to noise • Provides calibrated data, suitable for statistical analysis and manipulation for discovery • Emission filters allow additional multispectral fluorescence imaging, with excitation at each LED wavelength • Powerful, user-friendly hardware setup and image analysis software is central to the system Camera LEDs Integrating sphere Emission filter wheel Sample
- 8. © analytikLtd VideometerLab 3 Schematic
- 9. © analytikLtd Index of application areas 1. Sorting Categorising 1. Seafood sorting 2. Product composition 3. Pork fat percentage 2. Spoiling 1. Meat spoilage 2. Meat browning 3. Fruit oxidising 4. Biscuit burning 3. Quality Control 1. Seed contamination 2. Biscuit mishandling 3. Counterfeit packaging www.analytik.co.uk
- 10. © analytikLtd Sorting Seafood Sorting Back to Index5 • The traditional method of assessing salmon colouration is to use a colour chart. A human operator will offer his or her ‘best guess’ as to the colour of the salmon This salmon is a 27 on the SalmoFan chart opposite.
- 11. © analytikLtd Sorting Seafood Sorting Back to Index5 • The VideometerLab can be taught two extremes of salmon colouration, and then will false colour an image to represent what it has just learned (blue is the ‘pinkest’ a salmon can ever be, orange is the ‘reddest’)
- 12. © analytikLtd Sorting Seafood Sorting Back to Index5 • It can then apply this model to a real salmon, and will not make any of the mistakes the traditional methods will Colour in RGB False Colour Image (Human Vision) (Videometer ‘Vision’)
- 13. © analytikLtd Sorting Seafood Sorting Back to Index5 • Most usefully, a salmon that does not fall neatly onto an integer number can have its colour determined with up to two decimal places of accuracy
- 14. © analytikLtd Sorting Seafood Sorting Back to Index5 • Prawn sorting is done in the same way, with the same sorts of subjectivity problems, compounded by the fact there are many hundreds of prawns to be analysed at any one time
- 15. © analytikLtd Sorting Seafood Sorting Back to Index5 • The VideometerLab can separate touching prawns and automatically put them in the correct ‘bin’ to guide an operator later. In this image the VideometerLab has automatically ignored anything too small to be a prawn
- 16. © analytikLtd Sorting Product Composition Back to Index5 • In this image the operator wants to identify what percentage of this tuna steak is blood meat
- 17. © analytikLtd Sorting Product Composition Back to Index5 • The operator can either highlight the difference between blood meat on the left and other meat on the right and measure it with the onboard geometry tools or skip out the human element altogether and quantify the percentage automatically, as in the right-hand image
- 18. © analytikLtd Sorting Product Composition Back to Index5 • Similar techniques can be used on most heterogeneous substances, such as the morceau in this foix gras
- 19. © analytikLtd Sorting Pork Fat Percentage Back to Index • The VideometerLab can quantify the percentage of fat in this minced pork
- 20. © analytikLtd Sorting Pork Fat Percentage Back to Index • It does this by learning the spectral signature of fat and pork, then correlating the two
- 21. © analytikLtd Sorting Pork Fat Percentage Back to Index • In this experiment the VideometerLab performs excellently – it is always within 0.5% of the chemical test’s predictions VideometerLab%Estimate Chemical Analysis % Fat
- 22. © analytikLtd Spoiling Meat Spoilage Back to Index • The VideometerLab can be used for a variety of meat spoilage tests – here is one example looking for the number of bacterial colonies and discolouration of some mince after storage under different conditions
- 23. © analytikLtd Spoiling Meat Spoilage Back to Index • These images show just the UV (405nm) band to better highlight the size and distribution of the bacterial colonies No special storage Atmospheric Packaging M.A.P.
- 24. © analytikLtd Spoiling Meat Spoilage Back to Index • This histogram demonstrates quantitatively what is visually apparent on the last slide – MAP reduces the incidence and size of bacterial colonies • Sample 1 before storage • Sample 1 after atmospheric storage • Sample 2 before storage • Sample 2 after MAP storage
- 25. © analytikLtd Spoiling Meat Discolouration Back to Index • Alternatively, it can be used to predict browning, as with this sample of steak – the blue area shows higher levels of metmyoglobin which appears to predict discolouration
- 26. © analytikLtd Spoiling Fruit Oxidising Back to Index • The VideometerLab can be used as an objective measure of food spoilage
- 27. © analytikLtd Spoiling Fruit Oxidising Back to Index • The blue areas are browning, the red areas are unaffected. This can be quantified automatically by the VideometerLab software
- 28. © analytikLtd Spoiling Fruit Oxidising Back to Index • The VideometerLab can capture the whole browning process 1 5 10 15 20
- 29. © analytikLtd Spoiling Biscuit Burning Back to Index • In this slide the operator has taken a spectrum of the corner of each of these biscuits, and proved that the ‘blue’ biscuit (top left) has been burned during cooking
- 30. © analytikLtd QC Seed Contamination Back to Index • A human operator would be hard pushed to notice the single poppy seed contaminating this dish of sesame seeds. This could be fatal if instead of poppy seed it were a fragment of peanut, for example
- 31. © analytikLtd QC Seed Contamination Back to Index • Magnification of the previous image 1mm
- 32. © analytikLtd QC Biscuit Mishandling Back to Index • An operator handling this biscuit with wet fingers will spoil the taste, but may be difficult to spot if it is unexpected
- 33. © analytikLtd Multispectral Image Analysis • A variety of image processing tools are available in VideometerLab’s analysis software • Analysis protocols and models can be saved and applied to new samples for routine analysis • Multiple analysis models can be run on the same image data to quantify separate parameters • Analysis can be batch-run to aid in high-throughput data acquisition • Image archiving provides a record of samples for future data mining and regulatory compliance
- 34. © analytikLtd • Nuanced, human-like analysis of heterogeneous samples • Objective, accurate, repeatable measurements • Non-destructive analysis allows further sample assay work • No sample preparation is required • Rapid data acquisition and analysis enables high throughput screening Why use Multispectral Imaging?
- 35. © analytikLtd • Hardware options • Emission filter wheel (4 x 25mm Ø) for fluorescence macro-imaging • Dark- or Bright-field backlighting for scattering or translucency analysis • Bespoke solutions available • Software options • Image Processing Toolbox for filtering and segmentation of image data in individual spectral bands • Multispectral Imaging Toolbox for multivariate image analysis and modelling • Blob Toolbox for granular object separation, analysis and data output reporting • Matlab multispectral imaging toolbox integration Hardware and Software Options
- 36. © analytikLtd • Nuanced, human-like analysis of heterogeneous samples • Sophisticated data analysis tools for the novice and power user • Objective, repeatable data collection with easy export • Rapid, non-destructive testing with no sample preparation VL3 Multispectral Imaging adrian.waltho@analytik.co.uk Multispectral imaging at Analytik.co.uk VL3 Datasheet PDF