학술논문

Identification and Detection of Surface Defects of Outer Package Printed Matter Based on Machine Vision
Document Type
Academic Journal
Source
펄프·종이기술. 2020-04 52(2):3-11
Subject
Machine vision
print
defect detection
image processing
Language
Korean
ISSN
0253-3200
Abstract
In the printing process, the surface of the outer package printed matter is prone to defects such as chromatic aberration and misting, leading to a defective product. It is necessary to take an effective method to identify and detect surface defects in printed matter. In this paper, the application of machine vision technology in the detection of defects in outer package was studied. Firstly, a machine vision image acquisition device based on charge coupled device (CCD) camera was designed; secondly, the obtained image was processed by graying the average method, then OTSU binarization was performed after denoising by median filtering, and finally an improved differential matching method was designed for defect detection. The example analysis showed that the clear defect image of the outer package could be obtained by using the method proposed in this paper. The detection rate of the method in detecting 2,000 images reached 99.4%, and the average detection time was 103 ms. In the detection of 5,000 images, the detection rate of the manual detection method was 81%, but the detection rate of the method proposed in this paper was 99.1%. The experimental results proved the reliability of the method and provided some theoretical basis for the further application of defect detection technology based on machine vision in the print industry, which was conducive to the good development of the print industry.