Cotton pest identification and classification method and device

A technology for identifying and classifying pests, applied in character and pattern recognition, image analysis, image data processing, etc., can solve problems such as excessive calculation, achieve accurate identification and classification, and reduce economic losses

Inactive Publication Date: 2018-12-28
LUDONG UNIVERSITY
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Problems solved by technology

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  • Cotton pest identification and classification method and device
  • Cotton pest identification and classification method and device
  • Cotton pest identification and classification method and device

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Embodiment Construction

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0026] In the embodiment of the present invention, considering the shortcomings of chemical control methods in field pest control, in order to better combine machine vision and biological control methods to improve the effect of pest control, the embodiment of the present invention provides a method based on digital image processing Identification...

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Abstract

The embodiment of the invention provides a method and a device for identifying and classifying cotton pests. The method obtains an original image containing cotton pests to be classified, and obtainsHu invariant moment parameters of the original image and overall contour characteristic parameters of cotton pests to be classified. Based on Otsu threshold segmentation algorithm and Canny edge detection algorithm, the image of cotton pests to be classified is separated from the background of the original image, the wing image is extracted from the original image, and the wing contour characteristic parameters of cotton pests to be classified are obtained according to the wing image. Mathematical morphology algorithm is used to optimize the wing image and extract the corresponding mathematical morphological parameters of the wings of cotton pests to be classified. Radial basis function neural network is used to classify cotton pests. The method and the device enable the identification andclassification of cotton pests to be more accurate, thereby playing an important role in the targeted control of cotton pests and reducing the economic losses caused by cotton pests.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of digital image processing, and more specifically, to methods and devices for identifying and classifying cotton pests. Background technique [0002] Cotton is an important economic crop. With the rapid development of the cotton industry, new breakthroughs have been made in cotton science and technology; however, the technology of cotton pest control has not improved much, resulting in huge losses caused by cotton pests and diseases. There are many types and large numbers of pests in cotton fields. The backward identification method of cotton pests is an important reason for the slow development of cotton pest control technology. Moreover, the current identification and classification methods for cotton pests are single, and there is a lack of scientific, reasonable and accurate classification methods for cotton pests. [0003] The prior art provides a method for identifying and classi...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46G06T5/00G06T5/30G06T7/13G06T7/136
CPCG06T5/002G06T5/30G06T7/13G06T7/136G06T2207/20032G06T2207/20084G06T2207/30188G06V10/44G06F18/23
Inventor 曲海平张颖岳峻李振波寇光杰张志旺
Owner LUDONG UNIVERSITY
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