Mobile rice leaf nitrogen content detecting and grading method based on machine vision, system and computer readable storage medium

Abstract

The invention discloses a mobile rice leaf nitrogen content detecting and grading method based on machine vision. By using analysis on the correlation between optical indexes provided by a digital image and a rice leaf nitrogen content, quick and mobile rice leaf nitrogen content detection is realized. The machine vision technology is used, the processing technical scheme is transplanted to a mobile intelligent terminal, simple, convenient, low-cost, real-time, dynamic and quick analysis and detection on the rice leaf nitrogen content can be realized, a background comparison method is innovatively adopted, the inconvenience brought to leaf image acquisition by the previous cluttered background is solved, and interference generated when a target leaf image is extracted in the cluttered background can be effectively solved.

Description

technical field [0001] The invention relates to the interdisciplinary fields of artificial intelligence, pattern recognition and agricultural informatization, and in particular to a machine vision-based method, system and medium for detecting and classifying the movement of nitrogen content in rice leaves, which are suitable for quality evaluation of rice products. Background technique [0002] Rice is one of the three major food crops in the world and is the staple food for nearly half of the world's population. In China, rice production accounts for about 45% of my country's total cereal grain production. Since the 21st century, China's rice has shown a bad situation of "no growth in area, slow increase in per unit yield, low growth in total production, high growth in consumption, and rapid growth in imports". In order to avoid the food crisis, it is particularly important to increase the output and quality, and the stability of the output and quality has a crucial impact...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above problems, the present invention is to provide a light-weight, efficient, and expandable machine vision-based mobile detection and grading system and implementation method of rice leaf nitrogen content, which is used to solve the problem that the existing rice leaf nitrogen content detection method cannot protect samples , low efficiency, and inability to be widely promoted and other technical problems

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