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A method and system for image data quality control in field survey of crops

A quality control method and image data technology, applied in image data processing, image analysis, image enhancement, etc., can solve the problems of little research and quality control methods that cannot be used directly

Active Publication Date: 2020-11-24
CMA METEOROLOGICAL OBSERVATION CENT
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These elements are different from conventional meteorological elements, and traditional quality control methods cannot be used directly
At present, scientists at home and abroad mainly focus on crop segmentation algorithms and image feature extraction algorithms. There are few studies on crop images and crop growth characteristic parameters based on image recognition.

Method used

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  • A method and system for image data quality control in field survey of crops
  • A method and system for image data quality control in field survey of crops
  • A method and system for image data quality control in field survey of crops

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Embodiment 1

[0120] The classification model is a segmentation hyperplane.

[0121] In this example, given a set of point sets (features) in a separable space, there must exist a hyperplane π: ω·x+b=0 that can transform these features x i , i=1,...,n are divided into two different categories.

Embodiment 2

[0123] The classification model is a kernel function.

[0124] In this embodiment, for nonlinear classification problems, the processing method of SVM is to select a kernel function, and solve the problem of linear inseparability in the original space by mapping the data to a high-dimensional space.

[0125] In any of the above embodiments, preferably, the formulas of the first dark channel image and the second dark channel image are:

[0126]

[0127] Among them, J c Represents the image pixel value of the color channel c to which the coordinate value (x, y) belongs, Ω(x, y) represents the image block centered on the pixel (x, y), and (x, y) represents the coordinate value of the image pixel.

[0128] Such as Figure 11 As shown, the left column is the original image, and the middle column is the dark channel image corresponding to the original image. It can be seen from the figure that the gray value of the dark channel image of the polluted image is higher than that of...

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Abstract

The invention relates to an image data quality control method and system in crop live-action observation, and the method comprises the following steps: generating a gray value of an image missing graytone and an image incomplete rate of a corresponding image missing gray tone according to a historical image; Identifying an image missing amount of the to-be-detected image and an image missing ratecorresponding to the image missing amount according to the gray value; And comparing the image missing rate with the image incomplete rate. According to the technical scheme, the incomplete image inthe to-be-detected image is identified and eliminated by utilizing the color characteristic parameters of the crop image, namely the grey tone when the historical image is lost, so that the complete image is provided for subsequent calculation of the crop coverage and the leaf area index, and the calculation accuracy is improved.

Description

technical field [0001] The invention relates to the field of agricultural meteorological observation, in particular to an image data quality control method and an image data quality control system in field crop field survey. Background technique [0002] The real scene automatic monitoring system of crops is based on machine learning, image processing and wireless multimedia network technologies and methods, using CCD sensors, image collectors and communication devices to collect images of crops under natural light conditions and transmit them to computer terminals, through the built-in image recognition algorithm Extract image feature parameters, and then invert to obtain crop growth feature information. It has the advantages of 24-hour continuous work, high time resolution, non-contact, non-destructive, etc. It is a useful supplement to traditional agricultural meteorological observation, and has important application value in the field of agricultural disaster monitoring....

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/90
CPCG06T7/0002G06T7/90G06T2207/30168G06T2207/30188
Inventor 李翠娜白晓东余正泓许立兵
Owner CMA METEOROLOGICAL OBSERVATION CENT