Copper sheet and strip surface defect detection method based on-line sequential extreme learning machine

Abstract

Disclosed is a copper sheet and strip surface defect detection method based an on-line sequential extreme learning machine. The method includes the following steps that a copper sheet and strip surface image is captured through an image capturing module; the captured copper sheet and strip surface image is enhanced according to the median filtering method with the masking size of 7*7 to reduce noise in the copper sheet and strip surface image and the effect of the noise on the quality of the surface image; the copper sheet and strip surface image is subject to tophat transform treatment to reduce the effect of uneven illumination; a copper sheet and strip surface image pre-detection method based on eight-neighborhood difference values is adopted; defects in the surface image are segmented according to an image segmentation method, wherein it is judged that the copper sheet and strip surface image has the surface defects after pre-detection; geometrical characteristics, gray characteristics, shape characteristics, texture characteristics and other characteristics of each defect are extracted, and copper sheet and strip surface defect characteristic dimensions are subject to optimization and dimensionality reduction according to the principal component analysis method; a copper sheet and strip surface defect classifier based on the on-line sequential extreme learning machine is designed, and samples are used for training; characteristics of the copper sheet and strip surface image to be detected are extracted to identify types of the surface defects.

Description

technical field [0001] This patent relates to a method for detecting surface defects of copper strips by using computer vision technology. Background technique [0002] In my country, copper strip is an important variety of copper processing materials, which are widely used in electronic communications, machinery manufacturing, aerospace industry and other fields. In recent years, with the development of modern electronics, communications and semiconductor industries, the demand for low-end copper strip products has gradually shrunk, followed by the increasing demand for high-end products, and then a special proposal for the quality of copper strips The requirements of "precision copper strips" are met, that is, the copper strips have the quality requirements of "high surface, high performance and high precision". The surface quality of copper strip is an important indicator to determine the quality of its products. Due to the influence of factors such as production equipm...

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Problems solved by technology

[0005] In order to overcome the shortcomings of the existing computational vision technology in the detection method of copper strip surface defects, the present invention proposes a copper strip surface defect detection method based on an online sequence extreme learning machine

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