Coal-rock identification method based on image LBP

A coal rock recognition and image technology, applied in the direction of character and pattern recognition, instruments, computer components, etc., can solve the problem of easy to be affected by light, noise, viewpoint, sensor failure, increase the waste of manpower and material resources, etc. question

Inactive Publication Date: 2015-12-23
CHINA UNIV OF MINING & TECH (BEIJING)
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Problems solved by technology

The above methods have their own advantages and disadvantages, but they all use sensors for identification.
On the one hand, in different coal mining areas, different sensors need to be selected and installed on different machinery and equipment; on the other hand, in the coal mining environment, the sensors themselves are prone to failure and failure, which undoubtedly increases the manpower and waste of resources
[0004] In order to solve the above problems, image technology

Method used

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  • Coal-rock identification method based on image LBP
  • Coal-rock identification method based on image LBP
  • Coal-rock identification method based on image LBP

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Embodiment Construction

[0052] A kind of coal rock identification method based on LBP, comprises the following steps (flow process sees figure 1 ):

[0053] A. Under the same imaging conditions, collect a set of grayscale image sets of known coal samples and grayscale image sets of rock samples;

[0054] B. Apply 3 types of MB-LBP (Multi-BlockLocalBinaryPattern, multi-block local binary pattern) operators to the coal sample image set and rock sample image set respectively to obtain the coal sample image set and rock sample image set LBP (LocalBinaryPattern, local binary pattern) response image;

[0055] C. Calculate the gray level co-occurrence matrix of the LBP response image of the coal sample image set and rock sample image set

[0056] D. Respectively seek the energy, entropy, moment of inertia of the gray-level co-occurrence matrix of the LBP response image, and the mean value and standard deviation of the relevant 4 texture parameters as the final 8 texture features, and form a feature vector...

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Abstract

The invention discloses a coal-rock identification method based on image LBP. The method comprises the following steps: carrying out different observation and particle size analysis conversion on images to obtain LBP response images of the sample images; carrying out co-occurrence matrix calculation on the LBP response images to obtain gray-level co-occurrence matrixs of the LBP response images respectively; extracting characteristic values of the gray-level co-occurrence matrixs of the LBP response images respectively, and forming feature vectors; forming a characteristic matrix of the images according to the obtained feature vectors of the gray-level co-occurrence matrixs of the LBP response images; and on the basis of the template matching technique, comparing the image to be identified with each template, and the template, of which the matching degree is the highest, being the template of the image to be identified. The method is low in influence of illumination factor, good in stability and high in recognition rate.

Description

technical field [0001] The invention relates to an image LBP-based coal rock identification method, which belongs to the technical field of coal rock identification. Background technique [0002] Coal and rock identification is to use a method to automatically identify coal and rock objects as coal or rock. In the coal production process, the coal rock identification technology can be widely used in the production links such as drum coal mining, tunneling, caving coal mining, and raw coal gangue selection. Safe and efficient production is of great significance [0003] At present, there are mainly two types of methods for coal rock identification at home and abroad. The first is the measurement method of coal seam thickness, which adjusts the height of the roller through the feedback information, including various rays and electromagnetic waves, such as natural gamma ray detection method and electromagnetic wave detection method. And the radar detection method; the other i...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/50G06V10/758
Inventor 孙继平杨坤
Owner CHINA UNIV OF MINING & TECH (BEIJING)
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