Powerful Application of Machine Vision Technology-A Brief Analysis of the Working Process of Printin

 During the product printing process, due to process and other reasons, printed matter often suffers from chromatic aberration, inaccurate overprinting, and other appearance defects such as defective spots, ink lines, and black skin, resulting in the appearance of defective printed products. Printing companies generally use manual methods to sort defective products by sampling during printing and visually inspecting them one by one after printing. The detection efficiency is low, the cost is high, and the labor intensity is high.

With the continuous development of machine vision technology, the industry gradually uses machine vision systems to replace people to detect printed defects, which greatly improves production efficiency, reduces production costs, and empowers industry applications. Below, the editor of Xinxiwang will explain to you the main process of machine vision inspection and identification of printed appearance defects.

1. Image acquisition and preprocessing

During the image collection process, due to the influence of camera accuracy, lighting environment and other factors, the collected images will have a certain amount of random noise, resulting in image distortion. Here, a weighted median filtering algorithm is used that can remove sharp interference while maintaining edge details. Determine a window W with an odd number of pixels. First, weight each pixel in the window. The weighted value of a certain pixel is m, that is, the pixel is repeated m times when the window pixels are arranged in grayscale. Then each pixel in the window is grayed out. The intensity values are arranged from large to small, and then the intermediate value of the original image f(x, y) is replaced by the gray value at the middle position to obtain the enhanced image g(x, y). 

2. Visual inspection 

Visual inspection mainly consists of two parts, namely defect detection and identification. Printing defects are manifested in the image, which is the difference between the grayscale value of the defective part of the captured image and the standard image. Difference (pixel value subtraction) between the gray value of the collected image and the standard image, and determine whether the difference (the degree of difference in the gray value of the two images) exceeds the preset standard value range. This can be judged. There are no defects in the printed matter. 

The defect identification process, that is, after the difference is completed, a difference image with the same size as the collected image is obtained, and its pixel value is the difference between the corresponding pixels of each two images. Subsequently, the differential image is scanned line by line to detect defect points. When a defective pixel is encountered (its value is >0), the entire defective area is traversed recursively, and the size and size of the defective area are recorded at the same time. After the entire scanning process is completed, the number of recursions is the number of defects.

The PC-based machine vision system is used to replace manual inspection of printed matter, and the computer's high precision and fast speed are used to quickly and accurately detect the appearance defects of the printed matter, and conduct a comprehensive analysis of the degree of defects to determine whether the printed matter is defective or defective. Scrap. Compared with the detection and identification of appearance defects such as color difference and misprinting, which are much more difficult, the machine vision printing quality inspection system can improve intelligent information processing capabilities, greatly improve production efficiency and production automation, and effectively control Labor costs, and its industry applications will also gradually increase.