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Image segmentation method fusing superpixel block and overall nested edge

An image segmentation and superpixel technology, applied in the field of image processing, to achieve the effect of excellent segmentation performance and fast processing speed

Pending Publication Date: 2022-05-10
CHANGZHOU UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the small size of pests, traditional pixel-based methods take a long time to identify pests in images that often contain millions of pixels

Method used

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  • Image segmentation method fusing superpixel block and overall nested edge
  • Image segmentation method fusing superpixel block and overall nested edge
  • Image segmentation method fusing superpixel block and overall nested edge

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Embodiment Construction

[0050] The present invention will be further described below with reference to the accompanying drawings and embodiments. This figure is a simplified schematic diagram, and only illustrates the basic structure of the present invention in a schematic manner, so it only shows the structure related to the present invention.

[0051] like Figure 1-2 As shown, an image segmentation method that fuses superpixel blocks and overall nested edges includes the following steps:

[0052] S1: Input the image and define the number of seed points according to the target size of sugarcane aphids; the specific content is:

[0053] The input image is from an image dataset of grain sorghum leaves with sugarcane aphids taken with a camera under natural light in farmland (image resolution is 2448×3264); the vertical distance between the camera and the leaves is about 0.2 meters; this image data The set includes four light intensities: low light (light intensity less than 20kLux), strong light (li...

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Abstract

The invention relates to the technical field of image processing, in particular to an image segmentation method fusing a superpixel block and an overall nested edge, which comprises the following steps: S1, defining the number of seed points; s2, marking an edge probability graph E; s3, initializing seed points, and generating pre-segmentation; s4, generating an initial label L0 by using the spatial distance of the FSLIC and the color energy of the SEEDS; s5, according to the relation between E and L0, the edge of the super pixel is defined as a strong boundary or a weak boundary; s6, based on the weak boundary, according to the color energy, dividing the super-pixel edge again; and S7, outputting a sugarcane aphid image segmentation result. According to the invention, the probability edge graph and the fusion clustering strategy are introduced into the super-pixel segmentation method, and the advantages of the super-pixel method, such as high processing speed and capability of coping with the variability of natural illumination, are brought into full play; the superpixel segmentation method is efficient, reliable and excellent in segmentation performance.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image segmentation method for fusing superpixel blocks and overall nested edges. Background technique [0002] Sugarcane aphids were first identified in 2013 in Beaumont, Texas. Sugarcane aphids have high spreading ability and reproduction speed, and are very harmful to crops, and insect pests often break out every year. Therefore, efficient and rapid identification of pests is essential for farmers to quickly understand the extent of pest infestation and apply pesticides in a timely manner to avoid yield losses. [0003] The traditional main method of sugarcane aphids detection still requires grass-roots staff to enter the farmland to observe the distribution of aphids on the leaves, and rely on experience to judge the number level of sugarcane aphids on the leaves and diagnose the disease and insect pests in the area. This method has the characteristics of...

Claims

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Application Information

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IPC IPC(8): G06T7/12
CPCG06T7/12G06T2207/20081G06T2207/30188
Inventor 徐伟悦徐涛姬长英高书苑
Owner CHANGZHOU UNIV
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