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Publisert 2001

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Publikasjonsdetaljer

Tidsskrift : Scanning , vol. 23 , p. 165–174 , 2001

Utgiver : John Wiley & Sons

Internasjonale standardnummer :
Trykt : 0161-0457
Elektronisk : 1932-8745

Publikasjonstype : Vitenskapelig artikkel

Bidragsytere : Kohler, Achim; Høst, Vibeke; Ofstad, Ragni

Sak : 3

Har du spørsmål om noe vedrørende publikasjonen, kan du kontakte Nofimas bibliotekleder.

Kjetil Aune
Bibliotekleder
kjetil.aune@nofima.no

Sammendrag

Two feature extraction methods, the three-dimensional (3-D) local box-counting method and the area distribution method, are presented to describe the fat dispersion pattern on digital microscopy images of cryo-sectioned sausages. Both methods calculate whole arrays of variables for each microscopy image. The 3-D box-counting method calculates scale dependent (local) dimensions. This is in contrast to common fractal methods, which are univariate. Principal component analysis (PCA) was used to show that different sausages yield different fat dispersion patterns. Partial least square regression (PLS) shows that there is a correlation between the variables gained with both methods and the fat content.

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