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Proceedings Paper

Color image analysis technique for measuring of fat in meat: an application for the meat industry
Author(s): Lucia Ballerini; Anders Hogberg; Kerstin Lundstrom; Gunilla Borgefors
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Paper Abstract

Intramuscular fat content in meat influences some important meat quality characteristics. The aim of the present study was to develop and apply image processing techniques to quantify intramuscular fat content in beefs together with the visual appearance of fat in meat (marbling). Color images of M. longissimus dorsi meat samples with a variability of intramuscular fat content and marbling were captured. Image analysis software was specially developed for the interpretation of these images. In particular, a segmentation algorithm (i.e. classification of different substances: fat, muscle and connective tissue) was optimized in order to obtain a proper classification and perform subsequent analysis. Segmentation of muscle from fat was achieved based on their characteristics in the 3D color space, and on the intrinsic fuzzy nature of these structures. The method is fully automatic and it combines a fuzzy clustering algorithm, the Fuzzy c-Means Algorithm, with a Genetic Algorithm. The percentages of various colors (i.e. substances) within the sample are then determined; the number, size distribution, and spatial distributions of the extracted fat flecks are measured. Measurements are correlated with chemical and sensory properties. Results so far show that advanced image analysis is useful for quantify the visual appearance of meat.

Paper Details

Date Published: 4 April 2001
PDF: 12 pages
Proc. SPIE 4301, Machine Vision Applications in Industrial Inspection IX, (4 April 2001); doi: 10.1117/12.420903
Show Author Affiliations
Lucia Ballerini, Swedish Univ. of Agricultural Sciences (Sweden)
Anders Hogberg, Swedish Univ. of Agricultural Sciences (Sweden)
Kerstin Lundstrom, Swedish Univ. of Agricultural Sciences (Sweden)
Gunilla Borgefors, Swedish Univ. of Agricultural Sciences (Sweden)

Published in SPIE Proceedings Vol. 4301:
Machine Vision Applications in Industrial Inspection IX
Martin A. Hunt, Editor(s)

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