Fabric defect detection method based on distance matching function and perceptual hash algorithm

A perceptual hash algorithm, distance matching technology, applied in computing, image data processing, instruments, etc., to achieve the effect of fast computing

Active Publication Date: 2018-05-29
江苏知聚知识产权服务有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, for patterned fabrics, the different textures and patterns of fabrics and...

Method used

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  • Fabric defect detection method based on distance matching function and perceptual hash algorithm
  • Fabric defect detection method based on distance matching function and perceptual hash algorithm
  • Fabric defect detection method based on distance matching function and perceptual hash algorithm

Examples

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Embodiment

[0050] Embodiment: Select several types of common fabric defect images (holes, warp breaks, oil stains, scratches, etc.) from the fabric image library, and the size of the pictures is 256pixel×256pixel. Select some images, such as Figure 5 (first row). Using the algorithm of the present invention to obtain the structure feature map and the grayscale feature map, such as Figure 5 (second row, third row). Finally, the fusion feature map and defect segmentation image are obtained, where θ 1 =6, θ 2 =8, the result is as Figure 5 (line 4, line 5), the final result (line 6) is obtained, and it can be seen that the defect has been detected.

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 present invention discloses a fabric defect detection method based on a distance matching function and a perceptual hash algorithm. According to the method, the minimum period of a regular fabricis calculated through using the distance matching function, and the minimum period can be applied to obtaining image blocks; a repeat unit template is constructed, and the structure features of the template image block are extracted through adopting the perceptual hash algorithm; the structural features and grayscale features of image blocks of a sample to be tested are extracted, and are comparedwith the structural features and global gray average value of the template image block, so that a minimum Hamming distance feature image and a gray average value comparison feature image are obtained; and the merging and segmentation of the feature images are performed. The results show that the method of the present invention comprehensively considers the structural features and gray average value feature of the minimum period of the regular fabric, can effectively extract the defect area of the fabric and realize the defect detection of the fabric.

Description

technical field [0001] The invention belongs to the technical field of textile image processing, and in particular relates to a fabric defect matching detection method. Background technique [0002] Fabrics are the basis of everyday consumer products such as clothing, bags, bedding, medical fabrics and more. Fabric inspection is a critical part of quality control in textile production. Currently, most fabric inspections are performed by manual visual inspection which is costly, but unreliable due to human error and eye strain. The automatic visual inspection (AVI) of fabrics applies computer vision technology, which not only provides an efficient, low-cost and accurate method to replace labor, but also expands the inspection capacity to cover a wider range of different fabric patterns, from the simplest The most complex fabric patterns are available. The goal of AVI is to detect and delineate the shape and location of any defects on the fabric surface during or after fabr...

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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IPC IPC(8): G06T7/00G06T7/11
CPCG06T7/001G06T7/11G06T2207/30124
Inventor 徐贤局顾敏明潘海鹏
Owner 江苏知聚知识产权服务有限公司
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