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Soil image brightness controllable enhancement method based on weighted Gaussian subtraction fitting

A technology of image brightness and Gaussian fitting, which is applied in the field of image processing, can solve the problems of impact, soil image inconsistency and natural light, and affect the accuracy of soil type recognition, so as to improve the accuracy and reduce the impact

Pending Publication Date: 2022-07-19
CHONGQING NORMAL UNIVERSITY +2
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AI Technical Summary

Problems solved by technology

[0002] Soil image recognition is used for research and analysis of soil. In the prior art, machine vision is generally used to collect soil images. However, when collecting soil images, it is generally in the field, and the soil images are subject to inconsistent natural light during the image collection process. Therefore, different soil images can be obtained, which seriously affects the accuracy of subsequent soil type identification. At present, there is no effective means to solve the above problems

Method used

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  • Soil image brightness controllable enhancement method based on weighted Gaussian subtraction fitting
  • Soil image brightness controllable enhancement method based on weighted Gaussian subtraction fitting
  • Soil image brightness controllable enhancement method based on weighted Gaussian subtraction fitting

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Embodiment Construction

[0077] The present invention is further described in detail below:

[0078] A method for controllable enhancement of soil image brightness based on weighted Gaussian subtraction fitting provided by the present invention includes the following steps:

[0079] S1. Collect soil images, and calculate the gray-level probability density P of the Y component of the soil image org (y):

[0080] P org (y)=y fre / h·w;

[0081] where y represents the Y component gray level y∈[y a ,y b ], y fre Indicates the frequency of gray level y, h is the height of the image, and w is the width of the image;

[0082] S2. Build a soil image Y-component histogram based on the Y-component gray level of the soil image and the gray-level probability density; in this step, an existing method is used for the construction of the Y-component histogram, which will not be repeated here;

[0083] S3. Determine the domain of the Y component of the soil image as [y a ,y b ], the threshold range represent...

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Abstract

The invention provides a soil image brightness controllable enhancement method based on weighted Gaussian subtraction fitting, and the method comprises the following steps: S1, collecting a soil image, and calculating the gray scale probability density Porg (y) of a Y component of the soil image; s2, constructing a soil image Y component histogram based on the Y component gray level and the gray level probability density of the soil image; s3, determining the definition domain of the Y component of the soil image as [ya, yb], and performing weighted Gaussian subtraction fitting based on the Y component histogram of the soil image to obtain a weighted Gaussian subtraction fitting curve of the Y component of the soil image; s4, performing brightness controllable enhancement processing on the basis of the weighted Gaussian subtraction fitting curve of the soil image Y component, and performing RGB conversion on the enhanced soil image to obtain an enhanced RGB soil image; through brightness controllable enhancement, soil images collected under inconsistent natural illumination conditions are adjusted, so that the soil images are very similar to real soil images collected under certain specific illumination conditions, and the method is used for machine vision soil type identification, thereby reducing the influence of different natural illumination conditions on soil image identification, and improving the subsequent soil type identification precision.

Description

technical field [0001] The invention relates to an image processing method, in particular to a method for controllable enhancement of soil image brightness based on weighted Gaussian subtraction fitting. Background technique [0002] Soil image recognition is used for soil research and analysis. In the prior art, machine vision is generally used to collect soil images. However, when collecting soil images, it is generally performed in the field, and the soil images are subject to inconsistent natural illumination during the image collection process. Therefore, different soil images can be obtained, which seriously affects the accuracy of subsequent soil species identification. At present, there is no effective means to solve the above problems. SUMMARY OF THE INVENTION [0003] In view of this, the purpose of the present invention is to provide a soil image brightness controllable enhancement method based on weighted Gaussian subtraction fitting, which can adjust the soil ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/40G06T7/90G06F17/18
CPCG06T5/40G06T7/90G06F17/18
Inventor 曾绍华赵秉渝王帅刘国一
Owner CHONGQING NORMAL UNIVERSITY
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