Fabric defect detection method and device

A detection method and defect technology, applied in measurement devices, neural learning methods, biological neural network models, etc., can solve the problems of low reliability of detection results and low calculation efficiency of detection algorithms, improve generalization ability, and save parameters. , to prevent the effect of overfitting

Pending Publication Date: 2020-03-17
WUHAN TEXTILE UNIV
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  • Claims
  • Application Information

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Problems solved by technology

[0006] In view of this, the embodiment of the present invention provides a fabric defect detection method and device to solve the problems of low calculation efficiency of detection algorithms and low reliability of detection results in the prior art

Method used

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  • Fabric defect detection method and device
  • Fabric defect detection method and device
  • Fabric defect detection method and device

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Embodiment Construction

[0073] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0074] Embodiments of the present invention provide a fabric defect detection method, such as figure 1 shown, including:

[0075] Step S10, obtaining a ResNet50 model.

[0076] In this embodiment, the ResNet50 model trained on the ImageNet dataset is downloaded through network resources.

[0077] Step S20, replacing the first classifier of the ResNet50 mod...

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Abstract

The invention discloses a fabric defect detection method and device. The method comprises the following steps: acquiring a ResNet50 model; replacing a first classifier of the ResNet50 model with a second classifier; obtaining a characteristic value of the fabric defect sample image; extracting a weight parameter of the ResNet50 model as an initial value; carrying out transfer learning on the ResNet50 model according to the characteristic value and the initial value to obtain a plurality of defect category identification models; and detecting the to-be-detected fabric image according to the multiple defect category recognition models. According to the embodiment of the invention, the problem that defect image samples are extremely lacked is solved by adopting transfer learning; specifically, ResNet50 model parameters trained on a large image data set ImageNet are adopted as improved ResNet50 network initial parameters in the embodiment of the invention, and then a top convolutional network is continuously retrained in a fabric defect sample image set, so that the top convolutional network is more suitable for fabric defect detection.

Description

technical field [0001] The invention relates to the technical field of textiles, in particular to a fabric defect detection method and device. Background technique [0002] Fabric defect detection occupies a very important position in the production of the textile industry. The price of defective fabrics will be reduced by 45%-65%. Therefore, defect detection is the last hurdle for finished fabrics to leave the factory and an important step in quality control in textile production. process. [0003] At present, the detection of fabric defects in the industry is still dominated by manual detection, the detection speed is only 5-20m / min, and the manual operation is easily affected by external factors, and the labor cost is high, and there are low efficiency, false detection, and missed detection rate. High defects, which make it difficult for manual detection to adapt to the needs of modern industrial production, so there is an urgent need for fast and accurate defect detecti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/00G06K9/62G06N3/04G06N3/08G01N21/88
CPCG06T7/0004G06T5/00G06N3/08G01N21/8851G06T2207/10004G06T2207/20021G01N2021/8887G06N3/045G06F18/214
Inventor 罗维平陈永恒陈军马双宝游长莉
Owner WUHAN TEXTILE UNIV
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