Digital Image Processing Technology in Automatic Detection of Printing Products

In today's multi-color printing, efficient development, people have higher requirements on the quality of printing products and printing efficiency, and one of the effective ways to improve the quality of printing products and printing efficiency is the detection of printed products. Today's printing processes mostly use amplitude-modulated dots as the most basic unit for printing images. Controlling dot changes is the key to controlling the quality of printed products.

There are many ways to measure the quality of printed products, of which the most commonly used is the detection of dot area rate. At present, the most commonly used method for quality inspection of printed products is the control strip detection. However, the disadvantage of this method is that it is impossible to know the ink supply quantity and dot size variation of each single-color dot, and it is impossible to fully and truly reflect the quality characteristics of the entire printed product. The quality monitoring cannot be implemented in all directions. Sometimes the identification of the human eye will result in the phenomenon of misconsequences due to the complexity of the image and the number of colors. In order to improve the printing control accuracy, Heidelberg. Manroland uses advanced technologies that directly detect printed images. The automation of printing product inspection is the future development trend, and applying digital image processing technology to the quality inspection of printing products is undoubtedly a new direction of development.

Digital Image Processing Technology and Its Importance

Image processing is to use a series of specific operations to change the pixels of an image to achieve a specific goal, such as making the image clearer, extracting certain information from the image, and so on. Digital image processing is the main method of modern image processing, with advantages of good reproducibility, high precision, wide application and flexibility. The content of digital image processing is very rich. Functionally, it can be divided into three categories: image quality improvement, image analysis, and image reconstruction. The processing of printed images is mainly image analysis and automation in industry. In the real industrial field such as on-line product inspection and production process control, the main technology used is image segmentation, which is a very important technology for image analysis and the main method for image processing of printed products.

In the process of research and application of images, people often only have interest in certain parts of the image, which generally correspond to certain specific areas in the image that have unique properties. In order to identify and analyze the target in the image, it needs to be separated from the image. Based on this, it is possible to further use the image to measure the target. Image segmentation refers to the technology and process of dividing an image into regions with specific characteristics and extracting the target. It has different titles in different application fields and is a main part of the image processing process, and it is also a difficult problem. In fact, although the research on image segmentation has a history of several decades and has made considerable progress and achievements, it has also been proposed such as edge detection. Regional division, neural networks, pattern recognition and other algorithms, but because of the different fields of application, the quality of images, there is no a completely universal method, and there is no complete and objective evaluation system.

In recent years, with the rapid development of multimedia technology, the extraction and application of color images has become more and more extensive, and the processing of color images has become more and more important. Compared to the grayscale image, the color image contains much more information, including not only brightness, but also hue, saturation, and other image information.

When dealing with color images, we must first select the appropriate color feature space. The color information contained in the color image can be a good representation of the characteristics of each part of the image, any image processing method can be through the color information in the image Color features to achieve. In general, each pixel value in a color image is given by the three primary colors R, G, and B. However, these three colors have a large correlation and do not exhibit the characteristics of the object well. The direct use of these variables often cannot Get the desired effect. In order to reduce the correlation between the feature components in the color feature space, people convert the image from RGB space to other device-independent color spaces through linear and nonlinear transformations, such as YUV, YIQ, Lab, LCH, etc. Which kind of space or space combination should be adjusted according to the actual situation.

In addition, there are suitable strategies and methods for processing images, which have a great influence on the processing effects. In practical applications, it is necessary to select a treatment method suitable for the space according to the color space in order to obtain satisfactory results.

Application of Digital Image Processing in Printing Inspection

In the printing process, many factors affect the final quality of the printed product, and directly reflected on the printed product is the change in the amount of ink supplied by the various outlets and outlets. The smallest imaging unit in the image is the pixel, passing day, G. B. The three primary color values ​​represent the image content, and the smallest image forming unit in the printed image is a dot. The image content is reproduced by the overprint of the dot ink. The size and shape of the dot directly affect the quality of the printed product. In actual printing, people usually observe and calculate the dot area ratio and the ink supply condition of the printed image, compare it with the proofs to analyze the quality of the printed matter, and adjust the ink amount accordingly to improve the printing effect. However, the methods commonly used by people are still artificial and dependant. Even with the same printing plate, the dot changes in different ink areas and the supply of ink in the dots are not the same. If the acquisition equipment is used to directly collect the image data of the printed image and the collected digital image is processed accordingly, and the quality index of each monochrome ink dot is further obtained, the quality data of the entire image can be basically understood, and the printing can be further improved. The quality of the product, which is the basic idea of ​​automated testing of printed products. How to separate the dot image of each single-color ink from the color printing image, and then obtain the dot area rate and quality index of the monochrome ink dot image. It is the key to realize the automatic detection of printed products.

Color printing images are overprinted with four color inks C, M, Y, and K. Colors are mainly expressed by subtractive colorants. C, M, Y, K four colors can be composed of 16 kinds of basic color elements, these color elements as a color matrix. Comparing the color feature values ​​of each pixel in the printed image with the color feature values ​​of the parent body, and according to the principle of measuring the minimum color similarity from the distance, the pixel is classified, and the number of pixels included in each color parent and the original position thereof are counted. With the position in the image, the color of the dot image can be divided, and then each single dot image can be obtained.

The digital image processing technology is used to process the obtained color print image, and the four color values ​​of C, M, Y, and K are decomposed from the four-color overlaid image and copied into a blank image to obtain a four-color version. Dot image, and image processing on each color version, can get the dot area rate of each color version. Dot shape factor, dot position and other parameters. By comparing these information values ​​with standard values, you can analyze the problems that exist in current print products, such as the color difference, whether there are dirty spots, and whether the overprint is accurate. Then by the computer to make appropriate adjustments and feedback correctly or alarm, which can improve the printing control accuracy, reduce scrap rate, reduce the negative effects of human operations. In the experimental study, these data have high research value, and have important theoretical value for further research on the principle of color dot coloration and the study of ink overprinting rules.

Looking to future applications <br> <br> in actual printing, because printing water. The influence of ink causes the edges of the image to be blurred, and the acquisition device is affected by various conditions to make the input image unclear, etc., which will reduce the accuracy of the final color separation, thereby affecting the processing result. However, the use of digital image processing technology for the detection and monitoring of printed products still has a very large space for development, with the continuous development of image processing technology and more and more researchers involved, its role in the detection of printing products will be more The bigger it is.

The demand of the market has promoted the production and development of the quality inspection of printed products. The aim of automation is to guarantee the quality of printing products and the printing efficiency. Digital image processing technology has opened up a new path for the quality inspection and control of printed products.