Image-based automatic detection method of a cane stalk elongating stage and a maize jointing stage

Abstract

The invention, which belongs to the technical image of image detection, relates to a detection method, particularly to an image-based automatic detection method of a cane stalk elongating stage and a maize jointing stage. A complete growth period cane crop image and a complete growth period maize crop image are obtained; according to the obtained images, an image normalization exponential time sequence curve is calculated; on the basis of the image normalization exponential time sequence curve, a first-order derivative is calculated, so that time of entrance of a cane stalk elongating stage and a maize jointing stage can be determined based on a changing rule of the first-order derivative of the image normalization exponential time sequence curve. Therefore, the observation cost is lower and the observation difficulty is reduced. Whether the cane enters the stalk elongating stage and the maize enters the jointing stage can be detected automatically based on image features; and the detection result accuracy and practicability are high.

Description

technical field [0001] The invention relates to a detection method, in particular to an image-based automatic detection method for sugarcane stem elongation period and corn jointing period, belonging to the technical field of image detection. Background technique [0002] Sugarcane is one of the most important sugar crops and energy crops in China, and my country is the third largest sugar producer in the world. Corn is one of the important food crops and industrial raw materials in China. At present, my country's corn planting area and total output are second only to the United States, ranking second in the world. The production of sugarcane and corn plays a very important role in my country's agricultural and rural economic development and in increasing farmers' income. In order to improve the yield and quality of sugarcane and corn, it is necessary to understand their developmental speed and progress, and on this basis, analyze the relationship between their various deve...

AI Technical Summary

Problems solved by technology

[0005] However, due to the low resolution of remote sensing images, and they are easily affected by clouds, cloud shadows, and aerosols, only a single image can be used in a fixed area every day, which has great limitations.

It can be seen that the detection method based on remote sensing images is not a good choice for the automatic detection of sugarcane stem elongation period and corn jointing stage. At present, a method with high accuracy, strong practicability and convenient operation is needed to replace the sugarcane stem elongation period and corn jointing stage. Artificial observation method of corn jointing stage to obtain the accurate time of sugarcane stem elongation period and corn jointing stage, so as to guide agricultural activities in time

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