Workpiece surface defect detection method and device, electronic equipment and storage medium
A technology for workpiece surface and defect detection, applied in image analysis, image enhancement, instruments, etc., can solve the problems of small defect area, low detection accuracy and large resolution.
Active Publication Date: 2021-01-01
ZHENGZHOU JINHUI COMP SYST ENG
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(2) The defect area is small
[0005]
For the above sample picture, the feature of this sample picture is its large resolution and small defect area. Using the existing deep learning-based defect detection method for detection, its detection accuracy is low
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[0033] In order to further explain the technical means and effects of the present invention to achieve the intended purpose of the invention, a method, device, electronic device and storage medium for detecting surface defects of a workpiece proposed according to the present invention will be described below in conjunction with the accompanying drawings and preferred embodiments. , its specific implementation, structure, characteristics and effects thereof are described in detail as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field of the invention. The terms used herein in the descr...
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The invention relates to the technical field of workpiece surface defect detection, in particular to a workpiece surface defect detection method and device, electronic equipment and a storage medium.The workpiece surface defect detection method comprises the following steps of: preprocessing an acquired workpiece surface image to obtain an input feature map; performing feature extraction on the input feature map by using a convolutional neural network to obtain a plurality of feature maps; setting a feature storage module used for fusing multi-scale information behind at least one pooling layer at the network front end of the convolutional neural network; transmitting details to a high-level feature map in a skip dense connection mode according to the plurality of feature maps to obtain aplurality of prediction layers; and predicting different scales of prediction boxes for matching defect sizes according to the plurality of prediction layers. According to the workpiece surface defect detection method and the device, detail information such as texture of defects in the image is stored and transmitted through the feature storage module and a skip dense connection mode, so that thedetection precision of the surface defects is improved.
Description
technical field [0001] The invention relates to the technical field of workpiece surface defect detection, in particular to a workpiece surface defect detection method, device, electronic equipment and storage medium. Background technique [0002] Surface defect detection is an important guarantee for quality control in the industry and an important task in industrial manufacturing. However, various textured surfaces and defect shapes bring great challenges to defect detection. Traditional defect detection mainly relies on experienced professionals to identify, and the work efficiency is not high. Automatic defect detection methods can be broadly classified into two categories: classical detectors and deep learning-based detectors. Among them, classical detectors rely on manually extracted features to identify defects, such as SIFT, HOG and other features. Commonly used methods are statistical methods, structured methods, filter-based methods and model-based methods. Howe...
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Login to View More IPC IPC(8): G06T7/00G06N3/04
CPCG06T7/0004G06T2207/20221G06N3/045Y02P90/30
Inventor 徐明亮姜晓恒崔丽莎吕培李振宇张晨民闫杰李丙涛刘涛乔利稳
Owner ZHENGZHOU JINHUI COMP SYST ENG