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Rice leaf SPAD value estimation method and system based on computer vision

A computer vision and blade technology, applied in measuring devices, material analysis through optical means, instruments, etc., can solve problems such as low accuracy of estimation algorithms, high cost of instruments, and complex estimation algorithms, so as to improve estimation accuracy, High precision and the effect of eliminating differences

Active Publication Date: 2019-05-31
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0003] Purpose of the invention: In order to overcome the deficiencies in the prior art, the present invention provides a method for estimating the SPAD value of rice leaves based on computer vision, which can solve the problems of complex estimation algorithms, high instrument costs, and low accuracy of estimation algorithms. The present invention also provides a system for estimating the SPAD value of rice leaves based on computer vision

Method used

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  • Rice leaf SPAD value estimation method and system based on computer vision
  • Rice leaf SPAD value estimation method and system based on computer vision
  • Rice leaf SPAD value estimation method and system based on computer vision

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Embodiment 1

[0036] Introduction to RGB color space and HSV color space: According to the Beer-Lambert law analysis, it is found that there is a significant nonlinear correlation between the SPAD value in the middle of the rice leaf and the R, G, and B color components of the corresponding leaf image. The color change of rice leaves from turning green to full heading stage is consistent with the change trend of SPAD value in the middle and upper part of rice leaves, in which the leaf SPAD value has a significant correlation with the red component R value and the green component G value, and has no correlation with the blue component B value. obvious correlation. However, the existing research generally only selects the RGB color space for image color analysis.

[0037] The RGB color space belongs to the CIE standard chromaticity system and is the basis for displaying colors on digital devices. But the color difference that people see is the result of the combination of physical changes an...

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Abstract

The invention discloses a rice leaf SPAD value estimation method based on computer vision, and the method comprises the steps: (1) collecting a certain number of rice leaf samples, placing the rice leaf samples on a 18% gray plate, and obtaining corresponding sample images; (2) determining SPAD values of all the sample images; (3) removing a gray plate part in the sample images by adopting a threshold segmentation method, and leaving a green leaf main body part; (4) extracting the color features of the sample images, and obtaining the color features in the RGB color space and the color features in the HSV color space in the sample images; (5) by taking a color component as input, establishing an SPAD value estimation model M'2 based on the color component by adopting a stepwise regressionanalysis method. According to the method provided by the invention, the SPAD value data of the whole rice leaf can be quickly obtained, the estimation result is relatively high in precision and smallin error, the working efficiency of manually detecting the SPAD value of the rice leaf can be reduced, and a basis can be provided for visual research of the rice leaf.

Description

technical field [0001] The invention relates to the intersecting field of computer vision technology and crop growth observation, in particular to a method and system for estimating the SPAD value of rice leaves based on computer vision. Background technique [0002] The color of plant leaves can indicate plant nutrients, water status, plant diseases, and leaf aging. It is an important basis for water and fertilizer management, plant growth diagnosis, and yield prediction in precision agriculture. SPAD (Soil Plant Analysis Development) chlorophyll meter is a SPAD value obtained by measuring the light transmittance coefficient of leaves in the range of red light and near-infrared light to determine the "greenness" of plant leaves. It is non-destructive, fast, and portable. It is often used It is used to reflect the chlorophyll content or nitrogen content of plant leaves. However, the SPAD chlorophyll meter can only measure point by point, and cannot quickly obtain the "green...

Claims

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Application Information

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IPC IPC(8): G01N21/84
Inventor 白晓东杨爱萍张坤段里成赵铭卓姜啸晨曹卉
Owner NANJING UNIV OF POSTS & TELECOMM
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