Leaf color detection-based plant growth condition monitoring method

A technology of plant growth status and plant leaves, applied in the field of computer vision technology and plant growth status monitoring, can solve the problems of damage to leaves, high cost, cumbersome steps, etc., and achieve the effect of strong versatility and high accuracy

Inactive Publication Date: 2017-05-31
浙江省柯桥中学
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These methods require harvesting leaves, crushing and immersing in extracts, and quantitative analysis by expensive instruments
This traditional method for measuring chlorophyll content takes a long time, and the steps are cumbersome and costly. More importantly, it will damage the leaves.

Method used

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  • Leaf color detection-based plant growth condition monitoring method
  • Leaf color detection-based plant growth condition monitoring method
  • Leaf color detection-based plant growth condition monitoring method

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Embodiment Construction

[0042] Below in conjunction with example and accompanying drawing, the present invention will be further described.

[0043] like figure 1 Shown, the plant growth monitoring method that the present invention detects based on leaf color comprises the steps:

[0044] Step 1: Collect color images of the leaves of the plants to be monitored.

[0045] Step 2: Preprocess the leaf color image obtained in step 1, set the background pixels to white through the OTSU algorithm, and scale the leaf image to a uniform size, taking 50*50 as an example.

[0046] The implementation of the OTSU algorithm is as follows:

[0047]Note that t is the threshold for foreground and background segmentation, the proportion of foreground points in the image is w0, and the average gray level is u0; the proportion of background points in the image is w1, and the average gray level is u1.

[0048] Then the total average gray level of the image is: u=w 0 * u 0 +w 1 * u 1 , the variance of foreground an...

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Abstract

The invention discloses a leaf color detection-based plant growth condition monitoring method. On the basis of positive correlation between leaf color readings of plants and chlorophyll contents of the plants, the chlorophyll contents can be directly obtained through obtaining the leaf color readings. The method comprises the following steps of: obtaining plant blade images through shooting, and classifying plants by means of a pre-trained convolutional neural network classifier; analyzing colors of blades by using an image processing technology, and obtaining corresponding leaf color readings according to a model between leaf colors and leaf color readings, so as to obtain chlorophyll contents of the blades and obtain the growth conditions of the plants. Compared with the prior art, the method disclosed by the invention has the advantages of realizing lossless monitoring, having relatively strong reliability and being unconstrained by plant species.

Description

technical field [0001] The invention relates to the fields of computer vision technology and plant growth status monitoring, in particular to a method for monitoring plant growth status based on leaf color detection. Background technique [0002] In agriculture, in order to obtain better economic benefits or ecological benefits, it is often necessary to monitor the growth status of plants, and to take timely measures for plants with poor growth status. Chlorophyll content is inseparable from photosynthesis and nutritional status of plants, so in agriculture, chlorophyll content is often used as an indicator to judge the growth status of plants. The leaf color is essentially caused by the pigment in the plant, and chlorophyll, as an important pigment, is closely related to the leaf color. [0003] The accurate determination of chlorophyll content is very cumbersome, and the traditional methods mainly include spectrophotometer, near-infrared spectroscopy, and hyperspectral me...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/46G06K9/34G06N3/08
CPCG06N3/08G06V10/267G06V10/56G06F18/243
Inventor 章思怡杨军
Owner 浙江省柯桥中学
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