Textile defect detection method based on hierarchical clustering and Gabor filtering

A technology of hierarchical clustering and defect detection, which can be used in optical testing of defects/defects, measuring devices, material analysis by optical means, etc., and can solve the problem of low degree of automation.

Active Publication Date: 2017-05-31
CHANGZHOU UNIV
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Problems solved by technology

[0003] The technical problem to be solved by the present invention is: in order to overcome the deficiency that the existing automatic detection method of textile defects is still based on manual selection or manual definition, and the degree of automation is not high, the present invention provides a textile defect detection method based on hierarchical clustering and Gabor filtering , by combining based on hierarchical clustering (hierarchical clustering, HC) algorithm and Gabor filter group analysis based on the digital image pixel gray information of the flat textile surface under the illumination source, the textile surface defect is automatically located, and the present invention is particularly suitable for automatic identification in stable Textile surface imperfections in digital images of flat textile surfaces captured under illumination sources

Method used

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  • Textile defect detection method based on hierarchical clustering and Gabor filtering
  • Textile defect detection method based on hierarchical clustering and Gabor filtering
  • Textile defect detection method based on hierarchical clustering and Gabor filtering

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Embodiment Construction

[0046] The present invention is described in further detail now in conjunction with accompanying drawing.

[0047] In order to make the statement clear, some symbols and concepts involved in the present invention are now focused on defining.

[0048] 1. Represents a set of positive integers.

[0049] 2. Represents the set of integers including zero.

[0050] 3. Represents the set of positive real numbers including zero.

[0051] 4. Represents the set of real numbers including zero.

[0052] 5. T represents matrix or vector transpose.

[0053] 6. Express ratio small largest integer, such as

[0054] 7. Indicates that the sequence of operands is concatenated to produce a vector, such as a scalar v 1 = 1 and the vector for scalar s 1 =8,s 2 = 1, s 3 = 5, for vector

[0055] 8. in

[0056] 9. Cb(v 1 , v 2 ) represents a vector v with the same dimension 1 with v 2 The Chebychev distance (Chebychev distance).

[0057] 10.{a i} represents t...

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Abstract

The invention provides a textile defect detection method based on hierarchical clustering and Gabor filtering. A hierarchical clustering algorithm is combined with a Gabor filter set; digital image pixel gray-level information of a flat textile surface based on an illumination light source is analyzed to automatically position surface defects of a textile; the textile defect detection method comprises the main three steps of dividing a grid pattern, extracting characteristics and comparing the characteristics. The textile defect detection method provided by the invention is especially suitable for automatic recognition of textile surface defects in digital images, acquired under the stable illumination light source, on the flat surface of the textile; the textile defect detection method is a method for automatically dividing the grid pattern from the textile image based on the hierarchical clustering algorithm and carrying out characteristic extraction and defect recognition on the grid pattern based on the Gabor filter set.

Description

technical field [0001] The invention relates to a textile defect detection method based on hierarchical clustering and Gabor filtering. Background technique [0002] The accuracy rate of traditional manual recognition of textile defects is only 60-75% (K. Srinivasan, P.H. Dastoor, P. Radhakrishnaiah, et al.. FDAS: a knowledge-based framework for analysis of defects in woven textiles structures, J. Text. Inst. 83(1992) 431–448.), the method of machine automatic identification of textile defects has practical application requirements. Digital image samples of flat textile surfaces (hereinafter referred to as textile images) belong to two-dimensional textures, which have been shown to be generated according to pattern arrangements defined by 17 wallpaper groups (K. Srinivasan, P.H. Dastoor, P. Radhakrishnaiah, et al..FDAS: knowledge-based framework for analysis of defects in woven textile structures, J.Text.Inst.83(1992) 431–448.), the pattern used to generate two-dimensional ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/88
CPCG01N21/8851G01N2021/8887
Inventor 贾靓颜榴红
Owner CHANGZHOU UNIV
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