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# Multivariate Statistics in Image Analysis
## Highlight on Food Science
Opening example on application of multivariate statistics in food science: The fermentation process of salamis was monitored with the Videometer multispectral imaging system using 19 different spectral bands. The images in the first column are from days 2 and 42 after production shown as false colour composites based on three spectral bands (660 nm, 470 nm, 435 nm).The next column shows the meat and the fat phases at day 14 found by means of canonical discriminant analysis. Column 3 show images from day 2 and day 42 using a statistical meat colour scale designed to enhance fermentation stages. The darker blue is fresh meat, whereas yellow and orange represent darker red, fermented meat. The last column shows the coefficients for computing respectively the discriminant function and the colour scale values.
For more information see
[Camilla H. Trinderup, Flemming Møller, Anders Bjorholm Dahl, and Knut Conradsen (2018): Investigation of pausing fermentation of salamis with multispectral imaging for optimal sensory evaluations. Meat Science, vol. 146, pp. 9-17](https://www-sciencedirect-com.proxy.findit.dtu.dk/science/article/pii/S0309174017315279?via%3Dihub).
<div align="center"><a href="homepage.md"><img src="images/FigureSalamiCDA.png" alt="Fat and meat distribution in salami investigated bmo. CDA"></a></div>
## Multivariate Statistics
......@@ -35,6 +27,15 @@ Highlights with links to original papers and other material illustrated below in
- in-vivo dosimetry, and
- fibre directionality.
## Highlight on Food Science
Opening example on application of multivariate statistics in food science: The fermentation process of salamis was monitored with the Videometer multispectral imaging system using 19 different spectral bands. The images in the first column are from days 2 and 42 after production shown as false colour composites based on three spectral bands (660 nm, 470 nm, 435 nm).The next column shows the meat and the fat phases at day 14 found by means of canonical discriminant analysis. Column 3 show images from day 2 and day 42 using a statistical meat colour scale designed to enhance fermentation stages. The darker blue is fresh meat, whereas yellow and orange represent darker red, fermented meat. The last column shows the coefficients for computing respectively the discriminant function and the colour scale values.
For more information see
[Camilla H. Trinderup, Flemming Møller, Anders Bjorholm Dahl, and Knut Conradsen (2018): Investigation of pausing fermentation of salamis with multispectral imaging for optimal sensory evaluations. Meat Science, vol. 146, pp. 9-17](https://www-sciencedirect-com.proxy.findit.dtu.dk/science/article/pii/S0309174017315279?via%3Dihub).
<div align="center"><a href="homepage.md"><img src="images/FigureSalamiCDA.png" alt="Fat and meat distribution in salami investigated bmo. CDA"></a></div>
## Highlight: Change Detection in Earth Observation Data
### Multispectral Optical Data
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