O. Basset et al., Texture image analysis: application to the classification of bovine muscles from meat slice images, OPT ENG, 38(11), 1999, pp. 1950-1959
Image texture is analyzed to provide a series of features for the classific
ation of several sets of images. Images of meat slices are processed to cla
ssify various samples of bovine muscle as a function of three factors: anim
al age, muscle and castration. The different images present a particular te
xture that is a global representation of the connective tissue. The aim of
texture analysis is to extract specific features for each kind of meat. The
meat slices available for this study came from 19 animals, including 10 ca
strated animals. Their ages were 4 months (10 animals), 12 months (5 animal
s) and 16 months (4 animals). The same three muscles were studied for each
animal. The texture analysis was carried out on digitized images using the
first- and second-order statistics of the gray levels and morphological par
ameters, for the characterization of the marbling. Two classification metho
ds were implemented: the method of the k-nearest neighbors and a method bas
ed on neural networks. Both methods give comparable results and lead to sat
isfactory classification of the samples in relation to the three variation
factors. The correlation of the textural features with chemical and mechani
cal parameters measured on the meat samples is also examined. Regression ex
periments show that textural features have potential to indicate meat chara
cteristics. (C) 1999 Society of Photo-Optical Instrumentation Engineers. [S
0091-3286(99)01111-3].