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Crop image pest and disease damage region extraction method based on SLIC superpixels and automatic threshold segmentation

A technology of threshold segmentation and region extraction, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as large errors, repetitive work, and low measurement efficiency

Active Publication Date: 2019-08-13
HARBIN INST OF TECH
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Problems solved by technology

[0003] The purpose of the present invention is to overcome the shortcomings of low measurement efficiency, large errors, and repetitive work due to manual detection and statistical methods, as well as the limitations caused by human factors in the detection process, and then provide a method based on SLIC superpixels and automatic threshold segmentation. Extraction method of crop disease and insect pest area

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  • Crop image pest and disease damage region extraction method based on SLIC superpixels and automatic threshold segmentation
  • Crop image pest and disease damage region extraction method based on SLIC superpixels and automatic threshold segmentation
  • Crop image pest and disease damage region extraction method based on SLIC superpixels and automatic threshold segmentation

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[0049] The present invention will be further described below in conjunction with accompanying drawing and specific embodiment:

[0050] figure 1 It is a flow chart of the crop disease and insect pest area extraction algorithm based on SLIC superpixel and automatic threshold segmentation of the present invention. It includes the following steps:

[0051] Step 1: Image preprocessing: Median filtering is performed on the collected image data of crop diseases and insect pests to prevent noise interference.

[0052] Step 2: Determine the initial cluster center S 0 [s 1 ,s 2 ,...s s ]: select s cluster centers according to the equidistant L of the original image, and record the number of pixels in the original image as N, according to Determining s cluster centers is recorded as S[s 1 ,s 2 ,...s s ]. Calculate the gradient values ​​of all pixels in the 3×3 area around the s cluster centers, select the point with the smallest gradient value as the new initial cluster cente...

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Abstract

The invention discloses a crop image pest and disease damage area extraction method based on SLIC superpixels and automatic threshold segmentation, which relates to the field of crop pest and diseasedamage detection based on image processing. The method comprises the following steps: carrying out image preprocessing on uploaded image information, and segmenting an image into a plurality of superpixel regions according to an SLIC superpixel segmentation algorithm, thereby extracting edge information of pest and disease damage leaves; on the basis of a picture segmented into super pixels, combining super pixel areas through a histogram intersection method, so that crop leaves are extracted from background interference; finally, carrying out pixel point traversal on the leaves, using the principle that the image texture difference between a normal area and a pest and disease damage area in a leaf image is large setting automatic threshold iteration to segment the pest and disease damagearea from a healthy area. The method has high extraction precision and efficiency.

Description

technical field [0001] The invention relates to the field of crop disease and pest detection based on image processing, in particular to a method for extracting crop image disease and pest regions based on SLIC superpixels and automatic threshold segmentation. Background technique [0002] China is a large agricultural country. In the agricultural production that occupies a very important position in the development of the national economy, the prevention and control of crop diseases and insect pests is very important. In the prevention and control of pests and diseases, the first and most important problem is how to correctly identify the pests and diseases that harm crops during the growth of crops and, on the basis of correct identification, to reduce the damage caused by pests and diseases. To make an accurate analysis, therefore, it is necessary to extract the areas of crop diseases and insect pests for subsequent identification. At present, the detection of pests and ...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G06T7/136
CPCG06T7/0002G06T7/11G06T7/136G06T2207/20032G06T2207/30188Y02A40/10
Inventor 吴健宇李波尹振东吴芝路马波吴明阳
Owner HARBIN INST OF TECH
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