It allows us to utilize complex information provided by color machine vision systems in a more efficient way and also apply them to more universal tasks. A major problem with color machine vision is that during the camera operation the illumination conditions often vary due to numerous unexpected reasons. This makes it difficult to obtain stable color features for color recognition and measurements under real conditions. The objective of this study is to develop approaches to illumination invariant color machine vision in order to improve the performance of current color measurement and recognition techniques and to increase their domain of applications. A practical approach to on-line color camera calibration under changing illumination conditions has been developed.
Calibration is based on a color camera model and color constancy.
The first application area dealt with lumber inspection. For more details, see Spectral measurements of wood and Lumber grading. Research concerning applications in industrial color measurements has been carried out. A methodology for measuring very small color differences with a RGB color camera, based on physical color models and on-line camera calibration, has been developed. A pilot study dealt with the quality inspection of colored paper images.