Research on automatic monitoring and recognition method of crop growth status based on machine vision.

Abstract

Research on automatic monitoring and recognition methods for crop growth status based on machine vision is an important direction in the development of modern agriculture. By conducting real-time monitoring and recognition of the growth status of crops, it is possible to detect problems in crop growth in a timely manner and improve crop yield and quality. This method utilizes image processing and computer vision technology, extracts useful feature representations from images using deep learning methods, and classifi es the growth status of crops based on these features. This method is of great signifi cance, as it can not only improve agricultural production effi ciency and reduce production costs, but also improve the quality of agricultural products and bring more economic and social benefi ts to agricultural production. At the same time, this method also provides technical support for precision agriculture, achieving precise management and regulation of the farmland environment through monitoring and recognition of crop growth status, and improving the output effi ciency of farmland. In the future, with the continuous advancement of technology and the continuous expansion of application scenarios, the application prospects of machine vision technology in the agricultural fi eld will be even broader.