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Density peak clustering soil image shadow detection method based on histogram fitting

A shadow detection and density peak technology, applied in the field of image processing, can solve the problems of low accuracy, difficulty in ensuring soil image processing accuracy, large errors, etc., to achieve the effect of improving accuracy, avoiding error transmission defects, and ensuring accuracy

Pending Publication Date: 2021-12-17
CHONGQING NORMAL UNIVERSITY +1
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Problems solved by technology

[0003] In the prior art, clustering algorithms are used for soil shadow detection. However, the existing clustering algorithms have large errors in image segmentation processing, resulting in low final accuracy, and it is difficult to guarantee the processing accuracy of subsequent soil images.

Method used

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  • Density peak clustering soil image shadow detection method based on histogram fitting
  • Density peak clustering soil image shadow detection method based on histogram fitting
  • Density peak clustering soil image shadow detection method based on histogram fitting

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specific example

[0081] Such as figure 2 Shown: figure 2 To compare the existing algorithm with this method: the existing algorithm includes the use of traditional algorithm, DPC algorithm, EDPC algorithm, ACCDPC algorithm; the results are shown in Table 1 and Table 2:

[0082]

[0083]

[0084] Table 1

[0085]

[0086] Table 2

[0087] Among them, Table 1 shows the results of shadow detection (shadow and non-shadow segmentation) accuracy (described by brightness standard deviation); Table 2 shows the results of shadow detection performed 10 times, and the average time spent;

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Abstract

The invention provides a density peak clustering soil image shadow detection methodbased on histogram fitting. The method is characterized in that the density of the clustering data set is reconstructed, then the clustering center is adaptively determined, the segmentation threshold value based on the data points between the non-shadow region and the shadow region is dynamically determined, and a final shadow detection result is obtained, so that the method can effectively avoid the error transmission defect of a clustering data distribution strategy in an original clustering algorithm, can effectively improve the precision of soil shadow detection, and guarantees the accuracy of subsequent soil image processing.

Description

technical field [0001] The invention relates to an image processing method, in particular to a density peak clustering soil image shadow detection method based on histogram fitting. Background technique [0002] In soil detection and analysis, there are shadows in soil images collected by image equipment. In order to eliminate the influence of shadows on subsequent brightness normalization and soil type identification, shadow detection is a necessary preprocessing work. [0003] In the prior art, clustering algorithms are used for soil shadow detection. However, the existing clustering algorithms have large errors in image segmentation processing, resulting in low final accuracy, and it is difficult to guarantee the processing accuracy of subsequent soil images. [0004] Therefore, in order to solve the above technical problems, it is urgent to propose a new technical means. Contents of the invention [0005] A density peak clustering soil image shadow detection method ba...

Claims

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Application Information

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IPC IPC(8): G06T7/11G06T7/136G06T7/168G06K9/62
CPCG06T7/11G06T7/136G06T7/168G06T2207/20004G06T2207/30184G06F18/23211
Inventor 曾绍华王琪王帅刘萍
Owner CHONGQING NORMAL UNIVERSITY
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