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A Method for Extracting and Analyzing Yarn Appearance Feature Parameters in Multi-angle Mode

A technology of characteristic parameters and analysis methods, which is applied in the direction of material analysis, material analysis by optical means, and optical testing of flaws/defects, etc., can solve problems affecting the calculation of yarn hairiness quantity and length, contingency and error, etc., to achieve favorable Effects of extraction processing, enhanced grayscale contrast, and improved accuracy

Active Publication Date: 2021-06-29
SHANGHAI UNIV OF ENG SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, the existing method of image measurement and calculation of yarn hairiness is to calculate the image of a projection of the yarn. Since the shape of the yarn hairiness in the two-dimensional plane projection has great changes at different angles, the yarn hairiness is only collected from a single angle. Line image, the results of yarn hairiness parameters obtained from its analysis, there are large contingencies and errors, which affect the calculation of the number and length of yarn hairiness

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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  • A Method for Extracting and Analyzing Yarn Appearance Feature Parameters in Multi-angle Mode
  • A Method for Extracting and Analyzing Yarn Appearance Feature Parameters in Multi-angle Mode
  • A Method for Extracting and Analyzing Yarn Appearance Feature Parameters in Multi-angle Mode

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Embodiment 1

[0063] Embodiment 1: A method for extracting and analyzing yarn appearance characteristic parameters in a multi-angle mode, including:

[0064] Step 1. In the preprocessing step of several yarn images collected by yarn rotation 360 degrees, background processing is performed on yarn images collected by industrial cameras, and image tilt correction is performed, and image filtering processing is performed to obtain less background noise and yarn Grayscale image of the yarn with clear core and hairiness;

[0065] Step 2, the yarn grayscale image segmentation step, the preprocessed yarn image is subjected to yarn and background segmentation, and the yarn binary image is obtained;

[0066] Step 3, a morphological processing step, extracting the yarn core and yarn hairiness from the segmented yarn binary image;

[0067] Step 4, the step of counting yarn hairiness length and quantity, analyzing and calculating the yarn binary image after the morphological processing step and output...

Embodiment 2

[0124] Embodiment 2: A method for extracting and analyzing yarn appearance feature parameters in a multi-angle mode. The difference from Embodiment 1 is that in step 3, the segmented yarn binary image is first processed with diamond structural elements , and then use the Diamond structure element to process the yarn binary image again, and make a difference between the reprocessed yarn binary image and the original segmented yarn binary image to obtain the corroded yarn hairiness , refine the binary image after the difference, and then differentiate the obtained binary image with the original segmented yarn binary image to obtain a yarn binary image with hollow hairiness, and then use the disk structure element to After processing, a more accurate binary image of the yarn core can be obtained.

[0125] Using the disk structure element to open and close the yarn image can get a better yarn core image. In the experiment, it was found that when the disk structure element size is ...

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 method for extracting and analyzing yarn appearance characteristic parameters in a multi-angle mode. The key points of the technical solution are: a method for extracting and analyzing yarn appearance characteristic parameters in a multi-angle mode, which includes the following steps: Step 1. Yarn image preprocessing steps collected by 360-degree rotation of the yarn to obtain yarn grayscale images with less noise and clear yarn core and hairiness; step 2, image segmentation step, yarn grayscale image is divided into yarn and background to obtain yarn Line binary image; step 3, morphological processing step, extracting yarn core and yarn hairiness to the yarn binary image; step 4, yarn hairiness length and quantity statistics step, to the yarn 2 after the morphological processing step Value image analysis and calculation and output calculation results; step 5, count the yarn hairiness length and quantity in all yarn images collected by yarn rotation 360 degrees, and calculate the hairiness length and quantity of the yarn circumference. The invention can automatically and accurately extract and analyze the yarn appearance parameters.

Description

technical field [0001] The invention belongs to the textile field, and in particular relates to a method for extracting and analyzing yarn appearance characteristic parameters in a multi-angle mode. Background technique [0002] In recent years, with the technological innovation and progress of the textile industry, higher requirements have been put forward for the quality inspection of textiles. Factors affecting the appearance and quality of textiles arise at various stages of the textile production process, however the most common influencing factor is the quality of the yarn. In yarn quality testing, hairiness is one of the important indicators to measure the quality of yarn. Yarn hairiness has a significant impact on yarn performance, quality and subsequent processing. The traditional detection methods are divided into manpower detection and machine detection. The subjective factors of human detection are greatly affected, and the efficiency of machine detection is low...

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 Patents(China)
IPC IPC(8): G01N21/95G01N21/88
CPCG01N21/8851G01N21/95G01N2021/8887
Inventor 辛斌杰王文帝邓娜李佳平张学雨易亚男
Owner SHANGHAI UNIV OF ENG SCI
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