Tea tree freeze injury assessment method and system based on computer vision

A technology of computer vision and freezing damage, applied in the field of computer vision, can solve the problems of long time and strong subjectivity, and achieve the effect of improving accuracy

Pending Publication Date: 2022-03-11
QINGDAO AGRI UNIV
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AI Technical Summary

Problems solved by technology

At present, the identification of the degree of freezing damage in tea gardens mainly relies on manual observation and calculation, which is highly subjective and time-consuming

Method used

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  • Tea tree freeze injury assessment method and system based on computer vision
  • Tea tree freeze injury assessment method and system based on computer vision
  • Tea tree freeze injury assessment method and system based on computer vision

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Embodiment 1

[0046] A computer vision-based evaluation method for tea tree frost damage, the flow chart is shown in figure 1 , including the following steps:

[0047] Step 1. Image collection of tea tree frost damage:

[0048] In December 2020, images were collected at the Tea Research Institute in Rizhao City, Shandong Province (35°40′N, 119°33′E, 23m above sea level). The images of tea crowns were collected by CANON-EOS 6D. Images are stored in JPEG format with a resolution of 3024×4032. Shooting angles and distances are random.

[0049] Step 2, preprocessing the obtained images of the freeze damage of the tea trees.

[0050] First of all, the degree of frost damage of tea trees is classified into mild, moderate and severe. Table 1 shows the grading of the degree of frost damage of tea trees. Then, the resolution of the training image was adjusted to 1800×1800, and 640 enhanced photos were labeled with image labeler 9.2 in MATLAB software to obtain the training set. Levels 1, 2, a...

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Abstract

The invention discloses a tea tree freeze injury assessment method and system based on computer vision. The evaluation method comprises the following steps: acquiring a tea tree leaf freezing injury image through an RGB camera, preprocessing the image, identifying and grading tea tree freezing injury leaves by adopting a double-layer algorithm, in the first-layer algorithm, performing segmentation and first-time grading on the tea tree freezing injury leaves through a Faster RCNN network, and in the second-layer algorithm, performing second-time grading on the tea tree freezing injury leaves through a Faster RCNN network; and inputting the segmented pictures into a second-layer algorithm SVM for second-time grading, and finally evaluating the overall freezing injury degree of the tea tree according to the obtained grading conditions of the freezing injury leaves of different grades of the tea tree. According to the method, the freezing injury of the tea tree leaves can be identified, the freezing injury degree of the tea tree can be graded, the problems of high subjectivity and long time consumption of manual observation and evaluation of the freezing injury of the tea garden are solved, the model precision is improved, and the improvement of the management efficiency of the tea garden is facilitated.

Description

technical field [0001] The invention belongs to the field of computer vision, and in particular relates to a method and system for assessing freezing damage of tea trees based on computer vision. Background technique [0002] Tea tree (Camellia sinensis L.) is one of the most important economic crops in China, India, Sri Lanka, Kenya and other countries. However, with the continuous change of global climate and the vulnerability of tea trees to low temperature disasters, large areas of tea trees were frozen to death, which greatly reduced the yield and crop distribution in cold regions. Therefore, it is necessary to understand the situation of freezing damage in tea gardens, analyze the causes of freezing damage, and propose preventive measures. Then, disaster recovery is carried out to minimize the loss of tea production. [0003] The freezing process of tea trees is often first manifested on the leaves, and only in extreme cold conditions will the roots be damaged and di...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/10G06V10/22G06V10/26G06V10/50G06V10/764G06V10/774G06V10/82G06K9/62G06N3/04G06N3/08G06N20/00
CPCG06N3/04G06N3/08G06N20/00G06F18/2411G06F18/214
Inventor 丁兆堂李赫范凯王玉毛艺霖丁仕波宋大鹏
Owner QINGDAO AGRI UNIV
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