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Textile fabric fluff detection method based on deep neural network

A deep neural network, textile fabric technology, applied in the field of deep learning and neural network, can solve the problems of processing workers and affecting the quality of textiles

Inactive Publication Date: 2021-03-16
中山紫菜网络科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the textile machine is producing textiles, it is inevitable that the textiles will contain a large amount of wool, velvet and other sundries. If these sundries are not disposed of in time, they will affect the quality of the textiles, and will also cause troubles for workers in subsequent processing.

Method used

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  • Textile fabric fluff detection method based on deep neural network
  • Textile fabric fluff detection method based on deep neural network
  • Textile fabric fluff detection method based on deep neural network

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Embodiment Construction

[0046] Hereinafter, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Apparently, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described here.

[0047] Scenario overview

[0048] As mentioned earlier, when the textile machine is producing textiles, it is inevitable that the textiles will contain a large amount of wool, velvet and other debris. This creates confusion for workers, so it is necessary to test whether the textile needs fluff cleaning.

[0049] With the development of computer vision technology, the technology of extracting features in images through convolutional neural networks to detect dense objects in images is becoming more and more mature. Therefore, the idea of ​​the inventors of...

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Abstract

The invention discloses a textile fabric fluff detection method based on a deep neural network, and the method comprises the steps: obtaining a to-be-detected textile fabric image, wherein the to-be-detected textile fabric is a textile fabric in production; calculating the difference between the image of the to-be-detected textile fabric and the image of the textile fabric which is detected to bequalified on the texture level so as to obtain a texture difference feature map; inputting the texture difference feature map into a convolutional neural network to obtain a first feature map; equallydividing the first feature map into a plurality of image blocks according to different scales, wherein the sum of the number of the image blocks of the different scales is equal to the number of nodes of the input end of a full connection layer; and enabling the plurality of image blocks to pass through the full connection layer and the classification function to obtain a classification result, wherein the classification result is used for indicating whether the fluff quantity of the to-be-detected textile fabric meets a preset requirement.

Description

technical field [0001] The present invention relates to the technical fields of deep learning and neural network, and more specifically, relates to a method for detecting fluff of textile fabrics based on deep neural network, a detection system and electronic equipment. Background technique [0002] There are two types of textile fabrics: weft-knitted fabrics and warp-knitted fabrics. As one of the three elements of clothing, textile fabrics can not only interpret the style and characteristics of clothing, but also directly affect the color and shape of clothing. When textile machines produce textiles, it is inevitable that there will be a lot of wool, velvet and other sundries on the textiles. If these sundries are not disposed of in time, they will affect the quality of the textiles, and will also cause troubles for workers in subsequent processing. . [0003] At present, deep learning and neural networks have been widely used in computer vision, natural language process...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/001G06T2207/10004G06T2207/20084G06T2207/30124G06T2207/20021G06F18/24
Inventor 郑稹斌
Owner 中山紫菜网络科技有限公司