First, the basic principles and methods of microscopic image processing
The so-called microscopic image processing is to use microscope equipment to enlarge the details of images that are difficult for the human eye to distinguish clearly when acquiring image data, so as to obtain a magnified image. Then, a series of image processing methods and methods are used to process the microscopic images to obtain the expected index values, and compared with the traditional test results to find out the correlation between the two, thereby replacing the traditional man-made with digital technology. Unpredictable and controllable means of control.
1. Basic flow of microscopic image processing
2. Basic principles and basic algorithms of image processing
It is not possible to process a general image directly with a computer. Therefore, various types of image signals (photos, graphics, X-ray photos, etc.) should be first converted into digital images, that is, the digitization of images.
A monochromatic image can be viewed as a two-dimensional continuous function whose brightness appears as a continuous function of position, and the digital image in the computer is represented as a matrix. The different processing is to use different algorithms to operate on this image matrix. From the two-dimensional continuous function to the matrix, the function values ​​(brightness) are taken as samples in different spatial positions, and the quantification process of these samples is represented by a set of integer values. This is the sampling and quantification process of the image, that is, the digitization process. The digitized image is divided into many small areas, which are called pixels. The value of each pixel is represented by a luminance value or a gray value. For black and white images, there are only binary information, namely "black" and "white". In a computer, image information is represented by "1", and "0" indicates non-image information.
The original image is input to the computer through the image input device and becomes a discrete digital image, which can be expressed as a matrix:
For a dot microscopic image, it can be represented.
The "black" area represents a halftone image, and the "white" area represents a non-graphical area. As can be seen from the figure, the percentage of this dot can be seen as 13/25=50%, and the ratio of length and width is 1:1.
During image processing, such pixel matrixes are calculated and processed. General image processing methods include image smoothing, sharpening, image segmentation, binarization processing, edge tracking, and the like.
Second, offset quality control system
In an offset quality control system, the microscopic image is a test strip on a printed sheet, a proof sheet, or a printing plate. Using image amplification equipment, such as microscopic cameras or micro-cameras, to amplify the measurement and control bar 60 or 100 times, and then use digital equipment to capture binary information of the image to a computer at a certain frequency; use image processing software to image The information is processed to obtain a predetermined set of index values. Through the calculation and comparison, the control information of printing quality is obtained, and then these information are fed back to the printer water supply device, ink supply device, pressure adjustment device, jacket transfer adjustment device and other control devices through the computer, so that the printing conditions can be adjusted in time. And change.
The development of hardware has provided us with great convenience and practicality. At present, the microscopic magnification and digitization of the image can be completed with one device. The computer has become the most common device in the printing factory. For lithographic offset quality control systems, the image processing methods involved are very simple and common. Therefore, the realization of image processing software under the support of high-speed computers, real-time calculation and control is not a problem. A practical offset printing quality control system.
(to be continued)
The so-called microscopic image processing is to use microscope equipment to enlarge the details of images that are difficult for the human eye to distinguish clearly when acquiring image data, so as to obtain a magnified image. Then, a series of image processing methods and methods are used to process the microscopic images to obtain the expected index values, and compared with the traditional test results to find out the correlation between the two, thereby replacing the traditional man-made with digital technology. Unpredictable and controllable means of control.
1. Basic flow of microscopic image processing
2. Basic principles and basic algorithms of image processing
It is not possible to process a general image directly with a computer. Therefore, various types of image signals (photos, graphics, X-ray photos, etc.) should be first converted into digital images, that is, the digitization of images.
A monochromatic image can be viewed as a two-dimensional continuous function whose brightness appears as a continuous function of position, and the digital image in the computer is represented as a matrix. The different processing is to use different algorithms to operate on this image matrix. From the two-dimensional continuous function to the matrix, the function values ​​(brightness) are taken as samples in different spatial positions, and the quantification process of these samples is represented by a set of integer values. This is the sampling and quantification process of the image, that is, the digitization process. The digitized image is divided into many small areas, which are called pixels. The value of each pixel is represented by a luminance value or a gray value. For black and white images, there are only binary information, namely "black" and "white". In a computer, image information is represented by "1", and "0" indicates non-image information.
The original image is input to the computer through the image input device and becomes a discrete digital image, which can be expressed as a matrix:
For a dot microscopic image, it can be represented.
The "black" area represents a halftone image, and the "white" area represents a non-graphical area. As can be seen from the figure, the percentage of this dot can be seen as 13/25=50%, and the ratio of length and width is 1:1.
During image processing, such pixel matrixes are calculated and processed. General image processing methods include image smoothing, sharpening, image segmentation, binarization processing, edge tracking, and the like.
Second, offset quality control system
In an offset quality control system, the microscopic image is a test strip on a printed sheet, a proof sheet, or a printing plate. Using image amplification equipment, such as microscopic cameras or micro-cameras, to amplify the measurement and control bar 60 or 100 times, and then use digital equipment to capture binary information of the image to a computer at a certain frequency; use image processing software to image The information is processed to obtain a predetermined set of index values. Through the calculation and comparison, the control information of printing quality is obtained, and then these information are fed back to the printer water supply device, ink supply device, pressure adjustment device, jacket transfer adjustment device and other control devices through the computer, so that the printing conditions can be adjusted in time. And change.
The development of hardware has provided us with great convenience and practicality. At present, the microscopic magnification and digitization of the image can be completed with one device. The computer has become the most common device in the printing factory. For lithographic offset quality control systems, the image processing methods involved are very simple and common. Therefore, the realization of image processing software under the support of high-speed computers, real-time calculation and control is not a problem. A practical offset printing quality control system.
(to be continued)
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