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Method for segmentation of corps canopy image based on average dispersion

A mean shift, crop technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of high segmentation accuracy and unsatisfactory segmentation effect.

Inactive Publication Date: 2011-04-20
HARBIN ENG UNIV
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Problems solved by technology

[0005] Among these two types of methods, the semi-automatic method requires more manual intervention, but the segmentation accuracy is higher, and the automatic segmentation method does not require manual intervention, but the segmentation effect is not satisfactory.

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  • Method for segmentation of corps canopy image based on average dispersion
  • Method for segmentation of corps canopy image based on average dispersion

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Embodiment Construction

[0010] The following examples describe the present invention in more detail:

[0011] First, in order to improve the segmentation speed, the crop canopy image is resampled to reduce the image size. The specific method is: divide the original image F into r×r small areas, calculate the RGB color average value of each small area, use this color average value to represent the color of the small area, and obtain the processed image I. After such processing, the size of image I becomes 1 / r of image F.

[0012] Second, to extract different color features, the resampled image I is transformed into the HSI color space.

[0013] Then, four features are extracted for each pixel of the image I, namely: G-R, G-B, H, S, and each pixel of the image I is represented by a quadruple (G-R, G-B, H, S).

[0014] Finally, the crop canopy image is divided into crop and non-crop using the mean shift algorithm. At the same time, in order to speed up the calculation, the weighted average of the enti...

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Abstract

The invention provides a segmentation method for crop canopy images based on mean shift. The steps comprise firstly, re-sampling the crop canopy images in RGB color space, then, exchanging the crop canopy images in HSI space, next, indicating each pixel in the crop canopy images as a tetrad combined by four feature values, namely G-R, G-B, H, S, wherein R, G and B respectively indicate red weight, green weight and blue weight of pixel in the RGB space and H and S respectively indicate chroma and saturation of pixel in the HSI color space, then, employing mean shift algorithm to segment the crop canopy images into different types, finally, calculating the feature typical values of each type, if the first and the second components of the typical value are larger than zero, then, it is crops, if not, then, it is not crops. The invention has the advantages that parameters needed to be set is relatively less, the process of features extraction is simple, the algorithm is easy to be realized, and segmentation accuracy rate is high.

Description

(1) Technical field [0001] The invention relates to an image segmentation method, in particular to a crop canopy image segmentation method. (2) Background technology [0002] Many group characteristics of crops are also visual characteristics, so they can be analyzed using digital image technology. The so-called digital image technology refers to the use of computers to process, analyze and extract information from digitized images. A key step in analyzing crop population characteristics using digital image technology is image segmentation—segmenting crop canopy images into crop and non-crop (soil and residue). [0003] At present, two methods are used to segment crop canopy images using digital image technology—manual method based on image processing software and automatic method based on image segmentation technology. Among them, the manual method has high segmentation accuracy, but requires more manual participation and is inconvenient to use. Such methods include: Wan...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
Inventor 郑丽颖
Owner HARBIN ENG UNIV
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