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Feature extraction method of foam image texture based on multi-scale neighborhood correlation matrix

A neighborhood correlation matrix, foam image technology, applied in the field of image processing technology and pattern recognition, can solve problems such as inability to capture texture information

Active Publication Date: 2016-06-22
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the features extracted by using the neighborhood gray level correlation matrix can only reflect the single-scale spatial characteristics of the foam image texture, and cannot capture richer texture information from multiple scales.

Method used

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  • Feature extraction method of foam image texture based on multi-scale neighborhood correlation matrix
  • Feature extraction method of foam image texture based on multi-scale neighborhood correlation matrix
  • Feature extraction method of foam image texture based on multi-scale neighborhood correlation matrix

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Embodiment Construction

[0059] The present invention will be described in further detail below in conjunction with accompanying drawing and specific implementation example:

[0060] The specific embodiment of the present invention is described below in conjunction with accompanying drawing, there are three kinds of foams of different working conditions in a certain copper flotation site, are respectively normal foam, hydration foam and viscous foam, the foam images of these three kinds of different working conditions are as follows figure 1 shown.

[0061] The first step is to read the RGB foam image according to the foam video obtained at the copper flotation site, convert the RGB foam image to grayscale, and then perform wavelet decomposition on the foam grayscale image to obtain wavelet subgraphs on different scales;

[0062] Step 1: Read the RGB foam image from the original foam video;

[0063] Step 2: Grayscale the RGB foam image. The original RGB foam image is grayscaled into a foam grayscale...

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Abstract

The invention discloses a multi-scale neighboring dependence matrix-based method for extracting froth image texture characteristics. The method comprises the steps of firstly, performing wavelet transform on a froth gray level image; then, performing gray level mapping on wavelet approximating sub-image coefficients with different scales respectively; finally, statistically acquiring a new multi-scale texture characteristic for reflecting a froth image gray level change frequency statistical law according to a neighboring gray level dependence matrix, wherein the characteristic has relatively high robustness for reflecting a copper floatation production running state and divisibility suitable for working condition identification. According to the acquired texture characteristic, the froth images of different working conditions can be separated to achieve an aim of effectively identifying working conditions, and then operation guidance is provided for optimal control of floatation production.

Description

technical field [0001] The invention belongs to the field of image processing technology and pattern recognition, in particular to a foam image texture feature extraction method based on a multi-scale neighborhood correlation matrix. Background technique [0002] Correct identification of flotation conditions is the basis and key to realize the optimal operation of flotation production. The visual characteristics of flotation froth contain a large amount of information related to production operation variables and product quality, which is an important basis for judging the flotation effect. In the actual flotation process, the operator mainly judges the current working condition by observing the visual characteristics of the foam on the surface of the flotation cell. This method is highly subjective and arbitrary, which affects the accurate judgment of the working condition. [0003] With the rapid development of technologies such as machine vision and image processing, gr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/46
Inventor 彭涛赵林曹威娄洋歌赵璐宋彦坡韩华黄易
Owner CENT SOUTH UNIV
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