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An image analysis method based on principal component analysis and its application to fabric defect detection

A technology of principal component analysis and image analysis, which is used in instruments, character and pattern recognition, computer parts, etc., and can solve the problems of error in detection results, random interference of fabric textures without consideration, and large amount of calculation.

Active Publication Date: 2011-12-21
DONGHUA UNIV
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Problems solved by technology

It is worth noting that Kumar (2003) and Sezer et al. (2004) only regarded PCA as an auxiliary method for dimensionality reduction, while Ozdemir et al. (1996) directly used PCA for flaw detection, but the method Principal component analysis needs to be performed on each sample, which involves a very large amount of calculation; secondly, this method does not consider the random interference of fabric texture, and there are large errors in the detection results

Method used

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  • An image analysis method based on principal component analysis and its application to fabric defect detection
  • An image analysis method based on principal component analysis and its application to fabric defect detection
  • An image analysis method based on principal component analysis and its application to fabric defect detection

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Embodiment

[0066] The sample distribution of the six data sets used in the embodiment is shown in the table below:

[0067]

[0068] Among them, the training set A H and A V Respectively by the random vector x of step 1) h and x v Constituted, the number of samples in the present invention is uniformly taken as 600, which is used to calculate the corresponding pivot matrix; training set B H and B V Respectively by the y of step 2) h and y v Constituted, used to calculate the threshold T used for detection α ; test set D H and D V Respectively by the f of the flawed sample in step 3) h and f v Constituted to obtain the missed detection rate.

[0069] Figure 11 ~ Figure 16 The actual detection results of the six data sets used in the implementation are given, in which the false detection rate represented by the abscissa in each example is directly estimated by the confidence level α, and the missed detection rate represented by the ordinate is obtained by taking different c...

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Abstract

The invention belongs to the field of image analysis processing, is applicable to the field of automatic detection and control of the surface quality of fabrics, and relates to a method for analyzing an image based on principal component analysis and a method applicable to detection of the defects of fabric. The method for analyzing the image based on the principal component analysis comprises the following steps of: firstly, expanding gray values in an original image sample into two groups of vectors according to rows and lines; secondly, performing template operation on the two groups of vectors, and respectively performing principal component analysis on the two groups of vectors which are subjected to template operation to obtain corresponding principal component matrixes; and finally, performing projection operation on a sample to be detected by using the two principal component matrixes, and calculating the similarity of the sample after projection and the sample before projection to analyze the characteristics of the image. The invention has the advantages that: non-uniform illumination can be eliminated without the conventional pre-processing step; calculation in a detection period is simple; the original fabric sample is respectively expanded according to the rows and the lines and then subjected to template operation, so that the longitude and latitude orientation characteristics of fabric texture can be fully utilized, the defects can be highlighted, and the random interference of the texture is restrained; and detection accuracy rate is improved.

Description

technical field [0001] The invention belongs to the field of image analysis and processing and is applied to the field of automatic detection and control of textile surface quality. The invention relates to an image analysis method based on principal component analysis and a method for detecting fabric defects. Background technique [0002] Principal component analysis (PCA) or Karhunen-Loève (KL) transformation, as an important multivariate statistical method, is widely used in the field of pattern recognition, such as face recognition and data compression, due to its excellent properties. The basic idea of ​​principal component analysis is to use linear transformation to obtain a set of new features with the same number and no correlation with each other from the original features, and the first few of these features contain the main information of the original features. [0003] In the field of image analysis, principal component analysis, as a multivariate analysis metho...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/66
Inventor 周建汪军李立轻陈霞
Owner DONGHUA UNIV
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