A color calibration method for correcting the variations in RGB color values caused by vision system components was developed and tested in this study. Color calibration was performed through three procedures; characterization of machine vision components, optimal selection of illumination intensity and lens aperture, and pixel-based RGB color correction of additive and multiplicative errors. Color vision system components were characterized by the theory of image formation in machine vision. This procedure comprehensively provided the basic quantitative RGB characteristics of colors necessary for color calibration. A model of a color vision system was designed and a color chart was used as a reflectance object in test images. The theoretical RGB values of the color chart calculated by using the characteristics of the color vision system were matched to the actual ones within less than 5 gray levels. Also, based on the characteristics of vision system components, the quantitative RGB values of a color chart at a specific system configuration were transformed to those at different system configurations. The differences between the transformed and the actual RGB values were less than 5 gray levels. The test results showed that the method was effective in characterizing a color vision system. An optimal combination of illumination intensity and lens aperture for color image analysis was determined. The method was based on a model of dynamic range defined as the absolute difference between digital values of selected foreground and background color in the image. It was possible to estimate the non-saturating range of the illumination intensity (input voltage) and the lens aperture by using a model of dynamic range. The method provided an optimal combination of the illumination intensity and the lens aperture, maximizing the color resolution between colors of interest in color analysis, and the estimated color resolution at the combination for a given vision system configuration. The specific RGB characteristics of colors for color calibration were decided under the illumination conditions determined by this procedure. Based upon the results of the first two procedures, the variations in RGB values of colors caused by vision system components were estimated and corrected on a pixel basis in test images. The algorithm for color calibration was based upon the use of a standardized color chart. The RGB errors in color images were categorized into the multiplicative and the additive errors, according to the theory of image formation. The RGB errors of arbitrary colors in an image were estimated from the RGB errors of standard colors contained in the image. The RGB errors of arbitrary colors in test images were almost completely removed after color calibration. The maximum residual error was 7 gray levels under uniform illumination and 12 gray levels under nonuniform illumination. The test results showed that the developed method was effective in calibrating the variations in RGB color values caused by vision system components.A color calibration method for correcting the variations in RGB color values caused by vision system components was developed and tested in this study.
|Title||:||A Color Calibration Procedure for Machine Vision|