Identification of fat, protein matrix, and water/starch on microscopy images of sausages by a principal component analysis-based segmentation scheme
Publication details
Journal : Scanning , vol. 25 , p. 109–115 , 2003
Publisher : John Wiley & Sons
International Standard Numbers
:
Printed
:
0161-0457
Electronic
:
1932-8745
Publication type : Academic article
Links
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Kjetil Aune
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Summary
A color-based segmentation scheme applied to microscopy images of cryosectioned sausages is proposed. The segmentation scheme is capable of segmenting three different levels on the microscopy images: the fat particles, the protein matrix, and water/starch. The method is based on principal component analysis. A user-friendly program was developed for the manual segmentation of a selection of image pixels by microscopists. Principal component models based on the manually classified pixels are then used to segment fat, protein matrix, and starch/water on microscopy images. The program can also be used as a training tool for microscopists.
