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Because the traditional computer color matching algorithm can not give people an intuitive feeling, and the color matching process is difficult to understand, aiming at the above problems, an ink color prediction method and process were established. Firstly, the relative position of the ink color gamut in the CIEL*a*b* color space was determined by using the color gamut visualization technology. Then the position of the target color in the CIEL*a*b* color space and the ink color field was found, and the ink ratio of the target color was obtained by matrix calculation using the spectral data of the base color bar. The experimental results show that the method in this paper can meet the actual printing color requirements, and it can provide a new method for ink computer color matching.

The environmental pollution problems cause for people’s concern in recent years. Due to using environmental aqueous spot-color ink, flexographic printing shows a great potential, and the problem of high-precision flexographic printing color matching also becomes a hot topic. In this paper, the problem of computer color matching of flexographic printing aqueous spot-color ink was studied. Using flexographic IGT printability tester and yellow, magenta, cyan primary colors of ink to carry out color matching experiments and obtain the color samples by changing the concentration ratio of base ink. After utilizing the spectrophotometer to measure the chromatic, we take Kubelka-Munk theory as the guide theory, which studied the color model based on the theory of the new double constant Kubelka-Munk and the model of spectral matching based on weighting factor, and carried on the evaluation. The experimental results show that the spectral color model based on the weighting factor has higher precision of color matching in terms of color model of the new double constant Kubelka-Munk theory.

The goal of this paper is to improve the robustness of the tracking by detection system. We gain the aim by dynamic tuning the learning parameters for an accumulative learned classifier according to online performance evaluation. Firstly, two kinds of tracking loss measures are distinguished: one is positive due to object appearance variation which does not result in drift; the other is negative which really causes drift. Then, according to these two situations, different parameter updating strategies are proposed to maintain adaptive model updating. Our proposed algorithm adopts the ability of identifying track loss and controls the tracking process to enhance the stability and robustness of the original algorithm (CT), and experimental results show better performance with negligibly small additional running time on some challenging video fragments which original CT failed on.

This paper presents some results from an experiment of image softproofing under different International Color Consortium (ICC) rendering intents, which will be available for selecting an appropriate rendering intent in printing processes. In a screen softproofing procedure, image is converted via ICC profile embedded in image itself to output device profile, then to proofing device profile. With the rendering intent of absolute colorimetry in the second conversion, the effects of different rendering intents in the first conversion have been investigated through a softproofing software developed in Matlab 7.0. A variety of testing images, including light tone, shadow detail, etc., are used for image softproofing. The color differences between original images and proofed images are calculated under the S-CIE L*a*b* color difference formulae. Comparisons and analyses on the obtained images under four rendering intents show the effects of color characteristics of original images on rendering intent selection.

The aim of the investigation was to determine the influence of rendering intents on the gamut volume and the visual evaluations in digital proofing. According to that, the corresponding test form was used for the needs of investigation and printed on Epson style pro 7800 with the application of ICC standard rendering intents (perceptual, saturation, relative colorimetric and absolute colorimetric). Based on the results obtained by spectrophotometer measurements, the gamut of the digital proofing was illustrated with the ColorThink software in CIE L*a*b* color space. The analysis in relation to the results of visual evaluations shows the difference influence of the rending intents to digital image quality.