An evaluation of color spaces fordetecting defects in Douglas-fir veneer

Color information can be valuable for detecting and classifying surface defects inwood, but its usefulness depends on the color data's format and the analysis technique used. This study investigates five color transforms that convert the National Television Standards Committee red, green, and blue (RGB) primary color space into other potentially more useful spaces. A quadratic classifier was used to evaluate the relative utility of the different color spaces in separating defects from clear wood. Images of Douglas-fir veneer with encased knots, intergrown knots, and pitch streaks were converted to the various color spaces and then analyzed. The results show, for the conditions in this study, that a two-dimensional feature space is sufficient for classification and that there are no practically important differences in performance among the different color spaces. Thus, for images of Douglas-fir veneer, it appears that there is no advantage in mathematically transforming the original RGB data into another color space.