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Leaf image segmentation method and system based on color and morphological characteristics

An image segmentation and morphological feature technology, applied in image analysis, image enhancement, image data processing and other directions, can solve the problem of complex leaf background, and achieve the effect of good adaptability and robustness

Active Publication Date: 2020-09-18
SHANDONG UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although many segmentation algorithms have appeared, the inventors found that there is no general segmentation algorithm at present. In the segmentation of leaves based on field background, it is usually affected by factors such as light, weeds, and soil. Complex, and due to the interference of these factors, it is difficult to segment leaves from crop images

Method used

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  • Leaf image segmentation method and system based on color and morphological characteristics
  • Leaf image segmentation method and system based on color and morphological characteristics
  • Leaf image segmentation method and system based on color and morphological characteristics

Examples

Experimental program
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Embodiment 1

[0035] Such as figure 1 As shown, a leaf image segmentation method based on color and morphological characteristics of this embodiment includes:

[0036] S101: Cluster the crop plant images, retain the foreground area to which the leaf part belongs, and remove the background area.

[0037] The purpose is to segment the crop leaves in the picture, so the content in the picture is regarded as consisting of the foreground area and the background area, and the foreground area is the part of the leaf that needs to be segmented, and the background area is the irrelevant area to be eliminated.

[0038] In this embodiment, a Gaussian mixture model is used to cluster crop plant images. Gaussian Mixture Model (Gaussian Mixture Model), usually referred to as GMM, is a widely used clustering algorithm in the industry. It is composed of multiple single Gaussian distributions, and each single distribution becomes a component of the mixture model. Set the number of Gaussian components of the Gauss...

Embodiment 2

[0055] Such as figure 2 As shown, this embodiment provides a leaf image segmentation system based on color and morphological features, including:

[0056] (1) The clustering module is used to cluster crop plant images, retain the foreground area to which the leaf part belongs, and remove the background area.

[0057] The purpose is to segment the crop leaves in the picture, so the content in the picture is regarded as consisting of the foreground area and the background area, and the foreground area is the part of the leaf that needs to be segmented, and the background area is the irrelevant area to be eliminated.

[0058] In this embodiment, a Gaussian mixture model is used to cluster crop plant images. Gaussian Mixture Model (Gaussian Mixture Model), usually referred to as GMM, is a widely used clustering algorithm in the industry. It is composed of multiple single Gaussian distributions, and each single distribution becomes a component of the mixture model. Set the number of Gau...

Embodiment 3

[0075] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps in the method for segmenting a leaf image based on color and morphological characteristics as described in the first embodiment are implemented.

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Abstract

The invention belongs to the field of image segmentation, and provides a leaf image segmentation method and system based on color and morphological characteristics. The leaf image segmentation methodbased on color and morphological characteristics comprises the following steps: clustering crop plant images, reserving a foreground region to which a leaf part belongs, and removing a background region; screening out crop parts by using an ultra-green algorithm, and removing residual background regions; removing a weed area based on a processing method of a color difference value; removing adhered weed parts by adopting an area threshold method; and repairing and removing the image of the adhered weed part by using a closed operation, and finally obtaining a leaf image segmentation result.

Description

Technical field [0001] The invention belongs to the field of image segmentation, and in particular relates to a leaf image segmentation method and system based on color and morphological characteristics. Background technique [0002] The statements in this section merely provide background information related to the present invention, and do not necessarily constitute prior art. [0003] In recent years, with the continuous development of various image acquisition technologies, intelligent agriculture based on computer vision has attracted more and more attention. Agriculture is closely related to human life, and studying its leaves can not only get the growth status of the crop, but also predict its subsequent growth status and perform disease detection. The first thing to do in the above research is to segment the complete crop leaves. [0004] Many image segmentation algorithms have been proposed so far, including K-means, edge detection, watershed, saliency segmentation and othe...

Claims

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Application Information

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IPC IPC(8): G06T7/11G06T7/136G06K9/62
CPCG06T7/11G06T7/136G06T2207/30188G06T2207/10004G06F18/23
Inventor 杨公平张岩孙启玉刘玉峰谢丽娟
Owner SHANDONG UNIV
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