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Product surface defect detection method in industrial scene

A defect detection and industrial technology, applied in neural learning methods, image data processing, instruments, etc., can solve the problems of insufficient detection method accuracy, small defect detection, generalization and robustness, etc., to improve the accuracy , the effect of reducing the amount of design and enhancing the characterization ability

Pending Publication Date: 2022-04-15
上海交通大学宁波人工智能研究院
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Problems solved by technology

[0011] In view of the above-mentioned defects of the prior art, the technical problem to be solved by the present invention is how to solve the problem that the accuracy of the product surface defect detection method in the existing industrial scene is not high enough, especially the detection of small defects, generalization and robustness are not strong enough problems, and how to achieve a better trade-off between product surface defect detection speed and accuracy

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  • Product surface defect detection method in industrial scene
  • Product surface defect detection method in industrial scene
  • Product surface defect detection method in industrial scene

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Embodiment Construction

[0062] The following describes several preferred embodiments of the present invention with reference to the accompanying drawings, so as to make the technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned herein.

[0063] The existing product surface defect detection method in the industrial scene still has the problem that the accuracy of the product surface defect detection method is not high enough, especially the detection of small defects, the generalization and robustness are not strong enough, and how to achieve the speed of product surface defect detection and Accuracy is better trade-off problem.

[0064] In an embodiment of the method for detecting product surface defects in an industrial scenario provided by the present invention, improvements are made to the problems existing in the prior art from fo...

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Abstract

The invention discloses a product surface defect detection method in an industrial scene, and relates to the technical field of product surface defect detection and machine vision in the industrial scene, the method comprises the following steps: step 1, image acquisition: acquiring a surface image of a product on an industrial assembly line; step 2, image labeling: performing defect labeling on the surface image to obtain a surface defect data set; step 3, data enhancement: the surface defect data set is subjected to data enhancement, the data enhancement is a combination of one or more of the following data enhancement modes, and the data enhancement modes comprise random cutting, random horizontal overturning, random vertical overturning, scale jitter, color jitter, Mosaic or Mixup; 4, constructing a surface defect detection model; 5, training a surface defect detection model; and step 6, predicting the surface defect detection model.

Description

technical field [0001] The invention relates to the technical field of product surface defect detection and machine vision in an industrial scene, and in particular to a product surface defect detection method in an industrial scene. Background technique [0002] In industrial scenarios, efficient and stable quality inspection is an important part of the product manufacturing process. The speed and accuracy of quality inspection will directly affect the production capacity of the assembly line and the final quality of the product. Whether there is any defect on the surface of the product is an important basis to measure whether the product meets the requirements of industrial quality. In the process of industrial production and manufacturing, the detection of defects on the surface of products is mostly done through manual quality inspection, but manual detection methods require high labor costs, and there are high false detection rates and missed detection rates, which can...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/00G06N3/04G06N3/08
Inventor 王星庄开宇杨根科
Owner 上海交通大学宁波人工智能研究院
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