Presswork defect detection method based on deep learning

Abstract

The invention discloses a presswork defect detection method based on deep learning. The presswork defect detection method based on deep learning comprises following steps: A, a CCD industrial camera is used for image acquisition; B, defect images and defect-free images of different kinds are selected from the collected images as training samples; C, the training samples are adopted for off-line training of deep learning algorithm, so as to obtain connection weight values and offset parameters of a network model; D, the trained deep learning algorithm is adopted for on-line detection and identification of presswork image defects. According to the presswork defect detection method based on deep learning, presswork images are collected in printing process, the obtained images are subjected topre-treatment, and after pre-treatment, the images are input into the pre-trained defect detection model for defect detection, so that the presswork defect detection efficiency in production is increased.

Description

technical field [0001] The present invention relates to the technical field of printed matter defect detection, in particular to a method for detecting printed matter defects based on deep learning. Background technique [0002] With the advancement of modern technology and the development of information technology, printed matter is closely related to people's daily life, work and study. The progress of history is that people are pursuing higher and higher spiritual pursuits on the basis of satisfying material needs, and the appearance of printed matter is no exception. However, in the process of printing, due to the influence of some random factors, the surface of printed products On the surface, various defects often appear. In recent years, with the rapid development of computer technology and machine vision technology, printing defect detection technology based on machine vision and pattern recognition has emerged. However, these intelligent detection methods still use...

AI Technical Summary

Problems solved by technology

The progress of history is that people are pursuing higher and higher spiritual pursuits on the basis of satisfying material needs, and the appearance of printed matter is no exception. However, due to the influence of some random factors during the printing process, the surface of printed products , there are often various defects

In recent years, with the rapid development of computer technology and machine vision technology, printing defect detection technology based on machine vision and pattern recognition has emerged. However, these intelligent detection methods still use traditional image processing and recognition technology, and use manually selected features. Limited detection efficiency during printing

Images