Improving local composition measurements of binary mixtures by image analysis

Composition quantification in granular mixtures through colorimetric imaging is addressed. Digital images of binary mixtures have been analysed with three different colour spaces: gray scale, L⁎a⁎b⁎ and HSV. Experiments have been carried out on a small scale drum mixer. After blending, the mixtures have been impregnated with a binder, solidified and sliced. The colorimetric analysis has been carried out on the interior of the granular bed. Results obtained using the three colour-spaces have been performed and compared. The HSV colour space yields better results in terms of accuracy and computational effort. Effectiveness of HSV relies on its independence from shadows that are a distinctive feature of pictures of the three-dimensional granular surface. Very important, HSV does not require a calibration curve to convert colour information into composition, differently from the other colour spaces.