Originally published:2003-08 as Research report (Lincoln University (Canterbury, N.Z.). Applied Computing, Mathematics and Statistics Group) ; no. 05/2003 by Lincoln University. Applied Computing, Mathematics and Statistics Group.
As a result of constantly growing consumer expectations for meat quality, the meat
industry is placing more and more emphasis on quality assurance issues. Fat content in
meat influences some important meat quality parameters and meat marketability. Visible
fat includes marbling (intramuscular) and intermuscular fat. Chemical analysis is currently
used to determine the fat percentage in meat. However, this is a tedious, expensive and
time-consuming method. Some measurements, like the number, size distribution and
spatial distribution of marbling, are totally impossible by chemical analysis. For the meat
industry, it is very useful to have an accurate, reliable, cost effective, fast and nondestructive
technique to determine the fat content.
Computer vision has enormous potential for evaluating meat quality because image
processing and analysis techniques can quantitatively and consistently characterize
complex geometric, colour and textural properties.
The objectives of the present study were: a) to apply image processing techniques to
quantify fat content of beef and lamb steaks; b) to develop a relationship between the
chemical fat content and the fat content measured by image analysis.[Show full abstract]
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