Young grape sprout growing rate measuring system and method based on machine vision

Abstract

The invention discloses a young grape sprout growing rate measuring system and method based on machine vision. The system comprises a surveyor pole, a camera unit and a processing and controlling unit, wherein the surveyor pole is fixed beside a young grape sprout, the surveyor pole has a known length and serves as a length standard of image processing, the camera unit is fixed by a support unit, is directed at the young grape sprout and the surveyor pole, and is used for taking pictures containing the young grape sprout and the whole surveyor pole, the processing and controlling unit is used for controlling timing shooting of the camera unit and carrying out image processing and analysis on the pictures obtained, and the young grape sprout growing rate can be obtained by calculating the growing length of the young grape sprout between two times of shooting. The young grape sprout growing rate measuring system and method based on the machine vision is capable of measuring the growing condition of the young grape sprout in a self-timing and nondestructive mode, accurate in data, and capable of avoiding adverse impact of movement of a camera lens on a measurement result.

Description

technical field [0001] The invention relates to the field of machine vision, in particular to a system and method for measuring the growth rate of grape shoots based on machine vision. Background technique [0002] The shoot length and growth rate of grapes are important indicators for agricultural researchers to study grape growth. At present, in the actual application process, the measurement method for the length and growth rate of grape shoots is mainly manual measurement, that is, the operator uses a scale to measure the length of grape shoots at regular intervals every day, and uses the measured length and time to calculate shoot growth rate. This method is labor-intensive and it is difficult to guarantee the accuracy and completeness of the measurement data all day, especially at night due to the subjectivity of the measurement personnel. With the continuous development of machine vision technology, it has attracted people's attention as a non-destructive measuremen...

AI Technical Summary

Problems solved by technology

However, the current measurement system either needs to collect samples to affect the normal growth of new shoots, or needs to mark the measured target, which is difficult to achieve on grape shoots or easily causes errors.

In addition, most of the current systems use computers for image processing. Due to the harsh agricultural environment, computers are easily affected by high temperature, high humidity, rain, low temperature, etc., which is not conducive to 24-hour uninterrupted measurement on site, and general computers do not have special For the hardware structure of image processing, the real-time performance is not high and the design of image processing algorithm is complex, and the processing efficiency is low

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