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Warp Knitted Fabric Defect Detection Method Based on Wavelet Contourlet Transform and Visual Saliency

A wavelet profile and warp knitted fabric technology, applied in the field of image processing, can solve the problem of less fabric defect detection, achieve the effects of high practicability, avoid redundancy, and the method is simple and efficient

Active Publication Date: 2018-11-30
JIANGNAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This transformation is mainly used in image compression, image fusion and other fields, and is rarely used in fabric defect detection.

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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  • Warp Knitted Fabric Defect Detection Method Based on Wavelet Contourlet Transform and Visual Saliency
  • Warp Knitted Fabric Defect Detection Method Based on Wavelet Contourlet Transform and Visual Saliency
  • Warp Knitted Fabric Defect Detection Method Based on Wavelet Contourlet Transform and Visual Saliency

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Embodiment Construction

[0048] The present invention will be further described below in conjunction with specific drawings.

[0049] The warp knitted fabric defect detection method based on wavelet contourlet transform and visual saliency described in the present invention, such as figure 1 shown, including the following steps:

[0050]Step 1. Select the fundamental wave and construct the wavelet transform filter;

[0051] The two-dimensional discrete wavelet transform is an extension of the one-dimensional discrete wavelet transform, and it can complete its transformation process through two one-dimensional wavelet transforms. In its implementation, a two-dimensional discrete wavelet transform requires a two-dimensional scaling function and three two-dimensional wavelet functions ψ H (x, y), ψ V (x, y) and ψ D (x, y). These functions are also generalized applications of one-dimensional functions, and can be expressed as the product of two one-dimensional functions in principle. Its expressio...

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 relates to a warp knitting fabric defect detection method based on wavelet contourlet transformation and visual saliency. The method comprises the steps: selecting a fundamental wave, and constructing a wavelet transformation filter; performing wavelet decomposition for a warp knitting fabric image to be detected, and obtaining approximate feature sub-graphs and detail feature sub-graphs; performing Gauss difference among the approximate feature sub-graphs and the detail feature sub-graphs so as to obtain approximate feature difference sub-graphs and detail feature difference sub-graphs; performing normalization processing for the feature difference sub-graphs, and performing addition and mean value treatment to obtain approximate feature saliency graphs and detail feature saliency graphs; utilizing a non-subsample direction filter bank to perform convolution filtering for the detail feature saliency graphs to obtain detail feature direction sub-band coefficients, and selecting a higher sub-band coefficient with higher energy according to the energy theory to reconstruct the detail feature saliency graphs; and performing segmentation for the approximate feature saliency graphs and the reconstructed detail feature saliency graphs, adding each segmented images after processing the segmented images, and then performing defect determination. The warp knitting fabric defect detection method based on wavelet contourlet transformation and visual saliency can improve the defect detection accuracy.

Description

technical field [0001] The invention relates to a warp knitted fabric defect detection method based on wavelet contourlet transformation and visual salience, belonging to the technical field of image processing. Background technique [0002] In recent decades, the market share of warp knitted fabrics has continued to increase. Compared with woven and weft knitted fabrics, warp knitted fabrics are known for their high weaving efficiency and fast machine speed. Defects on warp knitted fabrics, such as common yarn breaks, crosspieces and oil stains, will have a great impact on its price, thereby affecting the actual benefits of the production enterprise. In the traditional defect detection, the on-line detection is carried out by the operator on the machine. This method is inefficient, and there are physiological limitations such as visual fatigue, and there are large errors in the actual effect. Compared with manual labor, the defect detection method based on machine vision ...

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): G06T7/00
CPCG06T7/0008G06T2207/20064G06T2207/30124
Inventor 李岳阳蒋高明丛洪莲夏风林夏栋
Owner JIANGNAN UNIV
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