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Fabric defect detection method

A detection method and fabric technology, applied in image data processing, instrument, character and pattern recognition, etc., can solve problems such as weak adaptability, insignificant detection effect, and difficulty in effectively describing complex and diverse fabric textures. Improve adaptability, effectively and accurately detect defects

Inactive Publication Date: 2019-07-05
XI'AN POLYTECHNIC UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Based on the above analysis, the existing detection methods are difficult to effectively describe complex and diverse fabric textures, and have high computational complexity and poor self-adaptability, resulting in inconspicuous detection results; There are various materials, how to effectively detect defects is still a research hotspot

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
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Experimental program
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Embodiment

[0078] A fabric defect detection algorithm based on the combination of improved weighted median filter and K-means clustering, specifically implemented according to the following steps:

[0079] Step 1, scale the fabric defect image to be detected to 256×256 pixels, and convert it into a grayscale image;

[0080] Step 2, carry out improved weighted median filter processing to the yarn image obtained after step 1;

[0081] Step 2.1, when processing a pixel p in the image I, only consider pixels within a local window R(p) of radius r centered on p, for each pixel q∈R(p), the weighted median filter is based on the corresponding The affinity of pixels p and q in the feature map f compares it with the weight W pq are associated, as shown in formula (1):

[0082] W pq =g(f(p),f(q)) (1)

[0083] where: f(p) and f(q) are features at pixels p and q in f. g is a typical influence function between adjacent pixels, which can be Gaussian exp{-||f(p)-f(q)||} or other forms;

[0084] S...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
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Abstract

The invention discloses a fabric defect detection method which specifically comprises the following steps: firstly, zooming a fabric defect image to be detected to 256 * 256 pixels, and then converting the fabric defect image into a gray level image; carrying out improved weighted median filtering processing on the fabric defect image obtained in the step 1; finally, using a K-means clustering tosegment the fabric defects. The filtering speed can be remarkably increased while the background textures of the fabric image are inhibited, and the defects of the fabric with different texture backgrounds can be effectively and accurately detected.

Description

technical field [0001] The invention belongs to the technical field of textile defect detection methods, and in particular relates to a fabric defect detection method. Background technique [0002] As raw materials for clothing, decorative medical, industrial, and aerospace military supplies, fabric is an indispensable material in life and industrial production. In fabric production, due to factors such as yarn defects, mechanical failures, manual operation errors, and production environment interference , fabric defects will inevitably occur. The existence of defects has a decisive impact on the quality and price of textile end products. If defective products are used in aviation, military and medical applications, it will cause immeasurable and irreparable losses. Therefore, fabric defect detection is particularly important. However, due to the complex texture structure of various fabrics, the similarity between noise and subtle defects is high, which greatly increases th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/00G06T3/40G06K9/62
CPCG06T7/0004G06T3/40G06T2207/20032G06T2207/30124G06F18/23213G06T5/92
Inventor 张缓缓马金秀景军锋李鹏飞
Owner XI'AN POLYTECHNIC UNIVERSITY
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