Scratch detection method and device, computer equipment and storage medium

Abstract

The invention relates to a scratch detection method and device, computer equipment and a storage medium. The method comprises the steps that a to-be-detected chip image is acquired, a first feature image set is determined based on the chip image and an improved VGG16 network in a trained scratch detection model, and the first feature image set comprises three feature images with different image sizes; based on the first feature image set and an additional feature extraction network in the trained scratch detection model, a second feature image set is determined, and the second feature image set comprises three feature images with different image sizes; and obtaining a scratch detection result based on the first feature image set, the second feature image set and the detection network in the trained scratch detection model. By adopting the method, the accuracy of carrying out scratch detection on the chip can be improved.

Description

technical field [0001] The present application relates to the technical field of defect detection, in particular to a scratch detection method, device, computer equipment and storage medium. Background technique [0002] With the development of electronic product technology, chips are the core components of electronic products, and the quality inspection of chips is very important. [0003] In the prior art, deep learning algorithms can be used to detect scratches on chips. However, in the prior art, based on deep learning algorithms, image sets of large target objects are used to train the neural network model. Among them, better scratch detection results can be obtained, but it is not suitable for small target objects such as chips, and the existing scratch detection methods are used to detect chip scratches with low accuracy. Contents of the invention [0004] Based on this, it is necessary to provide a scratch detection method, device, computer equipment and storage m...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, deep learning algorithms can be used to detect scratches on chips. However, in the prior art, based on deep learning algorithms, image sets of large target objects are used to train the neural network model. Among them, better scratch detection results can be obtained, but it is not suitable for small target objects such as chips. The existing scratch detection methods are used to detect chip scratches with low accuracy.

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