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Image texture identification method and system

A recognition method and image texture technology, applied in the field of image texture recognition, can solve problems such as loss of image gradient information

Inactive Publication Date: 2022-01-21
NANJING CHENXIAO SOFTWARE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the feature extraction process, there is often a situation where the gradient information of the image is completely lost.

Method used

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  • Image texture identification method and system

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Experimental program
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Effect test

Embodiment 1

[0056] In order to better aberfect the analysis requirements of image data during the work operation, the texture analysis of image features, this embodiment proposes an image texture identification method, such as figure 1 As shown, the method specifically includes the following steps:

[0057] Step 1, get image data during the job;

[0058] Step 2, encoding the image data;

[0059] Step 3, by the relationship between the image spatial position information and the image gradation, the positive calculation of the gradation value is calculated on the image local area, and the number of times the different LBP values ​​appear separately, respectively, and describes the texture characteristics of the image within the region. And the extraction of the texture characteristics of the encoded data;

[0060] Step 4, the extracted texture feature input image identification model is identified;

[0061] Step 5, the result of the output identification classification is used with respect to t...

Embodiment 2

[0072] In the further embodiment of the embodiment, when the image texture characteristic analysis is performed, since the gradation value of the two neighborhood pixels is small, it is in the zero difference edge, therefore, under the condition of strong illumination The binary sequence obtained in localized mode may have two extreme values, resulting in a conventional encoding method only depends on the gray value of the critical point of each group. For the above, the present embodiment is based on the central pixel point gradation value, generating LBP coding and LBP coding generated by two adjacent points as thresholds, by incorporating direction information of gray value between neighborhood points, A problem of poor LBP coding results in the traditional LBP operator is improved to a certain extent, and the overall LBP coding is improved.

[0073] Specifically, when obtaining the LBP value, divide the neighborhood points in the division area into two major classes depending ...

Embodiment 3

[0078] In a further embodiment of the embodiment, when the image data analysis is performed, the change in the lighting conditions is analyzed for the texture analysis, and the gradient information is fully lost, the present embodiment is distributed in the gradient direction. The characteristics of the shape, while constructing a graphics weight function based on the localized two-value mode, a weighting direction is generated in a weighted direction of the reference weight value of the pixel and its neighborhood; then, the collection of the matrix is ​​generated with each place offset to indicate local and part of the target. Global characteristics.

[0079] Specifically, the difference in different pixels in the image is different, and L is the number of quantized grades in the gradient direction. For the preset position offset (x, y), the expression of each pixel element is:

[0080]

[0081] In the formula Indicates the current pixel; Indicates the field of current pixels...

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Abstract

The invention provides an image texture recognition method and system. The method specifically comprises the following steps: step 1, acquiring image data in an operation process; step 2, encoding the image data; step 3, carrying out point-by-point calculation on gray values of local areas of the images according to the relation between the image space position information and the image gray values, respectively counting the occurrence times of different LBP values so as to describe texture features of the images in the areas, and carrying out texture feature extraction on the encoded data; step 4, inputting the extracted texture features into an image recognition model for recognition and classification; and step 5, outputting an identification and classification result for assisting the industrial operation process. The texture features of the image data are analyzed, and the image features are better extracted, so that the image analysis result better meets the requirement of real-time operation.

Description

Technical field [0001] The present invention relates to an image texture identification method and system, particularly the technical field of image data processing. Background technique [0002] The development of computer network information technology makes the analysis of image data into unacceptable analytical factors in modern industries. The extraction analysis using image features can greatly improve the efficiency of image analysis, so that the computer feedback to human information is more in line with human visual. [0003] In the prior art, when the image data analysis is performed, the texture feature is an important depiction of the image features, and therefore it is widely used to describe the smoothness, roughness of the target image. However, during the feature extraction process, there is often a case where the gradient information of the image causes full loss. Inventive content [0004] The present invention proposes an image texture identification method an...

Claims

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Application Information

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IPC IPC(8): G06T7/41G06T7/44G06T9/00G06V10/764G06V10/54G06K9/62
CPCG06T7/41G06T7/44G06T9/00G06F18/24
Inventor 张春美
Owner NANJING CHENXIAO SOFTWARE TECH CO LTD
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