Study on the Model of Chromaticity Closed-Loop Control for Print Online Detection

The print online detection technology contains wide range of content, for instance alignment inspection, defect detection and color detection, among them the color detection is the most difficult. In this paper, IGT printability tester is used to produce different ink film thickness samples of the yellow, magenta, cyan, black and map spot colors brown, blue, green, red, purple and other colors. Based on large number of experiment data collected, though mathematical modeling, data analysis, experimental validation and model updating, a closed-loop control model and techniques based on the chromaticity detection are proposed. By establishing the model of the relationship between the chromaticity value and the ink film thickness, the relationship between the ink film thickness and the ink key opening, the numerical calculation between the chromaticity and the ink key opening is achieved. The basic method of chromaticity closed-loop control is: when printing began, the model calculates the initial ink key opening with the ink preset algorithm, and set the ink key opening. After entering the print state, the model detects the RGB value of print by the machine vision technology, and converts the RGB value to CIE LAB values by color space conversion and gamut mapping. Then the model compares the Lab values with the standard values, determines whether the color-difference overrun. If the color-difference is within the allowable range, the model maintains the original amount of ink and ink key opening. If it exceeds the limit value, the model quickly calculates the deviation of the ink amount, and offers the ink key opening which is corresponding to the adjustment, feedbacks it to the print control center, resulting in the ink key response in order to achieve the real-time adjustment of the print ink amount. Compared with the control method of the ink amount based on density detection, the chromatic detection method is more accurate, and has better application prospects.