Latin American applied research
Print version ISSN 0327-0793
This article presents an alternative color-based classification methodology which is used for pattern recognition of pale lager beers. Beer sample images are digitalized on a common desk scanner resulting in color histograms in the RGB scale. The frequency distribution of color indexes according to each color channel were obtained for each image, then decomposed into vector lines R, G and B, each vector having 256 components (indexes/color tones). PCA is used to represent the data in two-dimensional plots, and also to represent color changes of beer samples exposed to light and air. After one hour, significant changes in the yellow color of the beer can be distinguished in the score plot. In short, differences between brands of beer are directly related to differences in their color.
Keywords : PCA; Chemical Imaging; Pale Lager Beers.