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Method for detecting wheat disease image in any direction based on feature reconstruction

An image detection and arbitrary direction technology, applied in the field of disease images, can solve problems such as image detection of difficult wheat diseases, and achieve the effects of enhancing robustness, accurate positioning, and improving accuracy

Pending Publication Date: 2022-04-29
HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI
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Problems solved by technology

[0004] The purpose of the present invention is to solve the defect that it is difficult to detect wheat disease images in any direction in the prior art, and provide a method for detecting wheat disease images in any direction based on feature reconstruction to solve the above problems

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  • Method for detecting wheat disease image in any direction based on feature reconstruction
  • Method for detecting wheat disease image in any direction based on feature reconstruction
  • Method for detecting wheat disease image in any direction based on feature reconstruction

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Embodiment Construction

[0078] In order to have a further understanding and understanding of the structural features and the achieved effects of the present invention, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:

[0079] like figure 1 As shown, a kind of arbitrary direction wheat disease image detection method based on feature reconstruction of the present invention comprises the following steps:

[0080] The first step is the acquisition and preprocessing of wheat disease images: acquire wheat disease images, manually label the acquired wheat disease images, use labeling software to create a rotating frame to frame the disease spot images and mark the disease spot categories, and establish a wheat disease training sample set .

[0081] Here, image acquisition equipment is used to shoot the front and back of wheat diseased parts in a field environment, and a number of images containing diseased spots are selected from the captured images as wh...

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Abstract

The invention relates to a feature reconstruction-based method for detecting a wheat disease image in any direction. Compared with the prior art, the defect that the wheat disease image in any direction is difficult to detect is overcome. The method comprises the following steps: obtaining and preprocessing a wheat disease image; constructing a wheat disease detection model; training a wheat disease detection model; obtaining a to-be-detected wheat disease image; and obtaining a wheat disease image detection result. According to the method, accurate positioning and rapid detection of wheat disease spot areas in any direction can be realized, the accuracy of wheat disease detection is improved, and the robustness of a wheat disease detection algorithm is enhanced.

Description

technical field [0001] The invention relates to the technical field of disease images, in particular to a method for detecting wheat disease images in any direction based on feature reconstruction. Background technique [0002] How to accurately detect and identify wheat diseases has always been a problem that plagues crop disease prediction and forecasting. In recent years, as a new breakthrough in the field of computer vision, deep learning methods have been used to deal with various problems in the field of agriculture. Many researchers have applied various deep learning techniques for crop disease recognition. Although these methods can perform crop disease detection tasks well, it is still challenging to obtain good detection results from wheat disease images in various challenging wild environments. [0003] Since the direction of the wheat lesion area in the field scene is arbitrary, applying a general horizontal detector to detect the lesion in any direction will l...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/40G06K9/62G06V10/774G06V10/764
CPCG06F18/241G06F18/214
Inventor 王儒敬刘海云焦林谢成军张洁杜健铭李瑞陈红波胡海瀛陈天娇
Owner HEFEI INSTITUTES OF PHYSICAL SCIENCE - CHINESE ACAD OF SCI