Fabric flaw automatic detection method based on Support Vector data description theory

A technology of support vector and data description, applied in the direction of optical testing flaws/defects, etc., can solve the problem of not guaranteeing the training samples and effective detection.

Inactive Publication Date: 2008-07-09
DONGHUA UNIV
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Problems solved by technology

It is obviously unreasonable to use two types of classifiers for single-class classification problems: th

Method used

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  • Fabric flaw automatic detection method based on Support Vector data description theory
  • Fabric flaw automatic detection method based on Support Vector data description theory
  • Fabric flaw automatic detection method based on Support Vector data description theory

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specific Embodiment

[0084] The present invention provides five specific examples to further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0085] Table 2 lists the distribution of relevant data for five datasets with different textured backgrounds.

[0086] 2 List of experimental samples

[0087]

sample allocation

Training set

test set

All normal samples

normal sample

flawed sample

total

Dataset 1

plain weave

6144

2544

528

3072

Dataset 2...

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Abstract

The invention belongs to the field of automatic detection and control of textile quality and particularly relates to a method for automatically detecting defects of textiles based on support vector data description theory. The automatic textile defect detection based on computer vision is a more difficult one-class classification task in real world. In the invention, support vector data description (SVDD) of the advanced one-class classification method is applied in the textile defect detection field for the first time to obviate the problems present in textile defect detection of conventional two-class classification support vector machine, which is difficult to collect representative defect samples completely and at larger number and further fails to effectively train the detector. Additionally, the invention provides a robust new method for solving the optimization problem of parameters, in particular to scale parameter of gauss kernel function, related in SVDD training. The automatic textile defect detection system based on SVDD can prospectively and conveniently control false alarm rate (false detection rate) in practice and can obtain lower miss ratio at lower false alarm rate.

Description

technical field [0001] The invention belongs to the field of automatic detection and control of textile quality, in particular to an automatic detection method for fabric defects based on support vector data description theory. Background technique [0002] The automatic detection of fabric defects based on computer vision is a research hotspot and difficulty in the application of modern intelligent technology to monitor product quality in the past one or two decades. The automatic detection of fabric defects belongs to the category of pattern classification in essence, specifically, it uses various modern information technologies to realize the identification of normal areas and defect areas in fabric images. At present, the vast majority of textile factories still use manual cloth inspection, which has many disadvantages, such as low detection speed, inability to implement real-time detection, and the labor cost, labor intensity, and missed detection rate involved are also...

Claims

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Application Information

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IPC IPC(8): G01N21/89
Inventor 步红刚汪军黄秀宝
Owner DONGHUA UNIV
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