Surface defect detection method and equipment based on three-dimensional image

Abstract

The invention provides a surface defect detection method and equipment based on a three-dimensional image. The method comprises the following steps: obtaining structured three-dimensional image data of a target object; extracting primary features from the structured three-dimensional image data to obtain a primary feature map of the target object; performing multi-scale feature extraction on the primary feature map to obtain a multi-scale feature map as large as the primary feature map; processing the primary feature map by adopting a pre-trained invalid pixel mask prediction network to obtain mask data as large as the primary feature map; performing feature cutting on the multi-scale feature map according to the mask data to obtain a feature map corresponding to the effective pixel; extracting high-level features from the feature map corresponding to the effective pixels to obtain a high-level feature map of the target object; and performing defect classification processing according to the advanced feature map to obtain a defect classification result of the target object. And invalid pixels are filtered out on the feature level, so that the efficiency is improved, and the accuracy is improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of image processing, and in particular, to a method and device for detecting surface defects based on a three-dimensional image. Background technique [0002] Surface defects refer to defects such as spots, depressions, scratches, defects, cracks, etc. that exist on the surface of a product, which not only affect the appearance of the product, but also affect the quality and performance of the product. Therefore, the detection of surface defects is of great significance, and has been widely used in industrial production, such as welding seam inspection, wafer inspection, etc. [0003] With the continuous development of image processing technology, the method of automatic detection of surface defects based on image data has gradually replaced the early visual inspection method performed manually. With the complexity of machine vision scenarios, 3D vision sensors are gradually put into p...

AI Technical Summary

Problems solved by technology

The three-dimensional image data output by the 3D vision sensor can provide more abundant information for surface defect detection, but due to the influence of the acquisition environment, such as occlusion, reflection, multiple reflections, etc., it often leads to the inability to obtain the height information of the pixel point, that is to say Invalid pixels usually exist in the 3D image data output by the 3D vision sensor

At present, the invalid pixels in the 3D image data are mainly processed through image restoration processing or image filling processing, which is not only inefficient, but also reduces the accuracy of surface defect detection.

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