Abstract:

To explore the relationship between the appearance characteristics of rice canopy and the nitrogen nutrition status of rice, the basic ideas and research progress of the application of computer vision technology in rice nitrogen nutrition diagnosis were summarized. This paper mainly discusses the acquisition of conventional rice nitrogen nutrition index, the acquisition and preprocessing of rice canopy image, the extraction and optimization of features, and the establishment of rice nitrogen nutrition diagnosis model. It is pointed out that the methods of rice canopy image acquisition, rice image processing and optimization of multiple comprehensive characteristics need to be further studied, and the methods of using machine learning to diagnose and model rice nitrogen nutrition need to be further explored. In the future, it is necessary to increase the application of computer vision technology in the research of rice nitrogen nutrition diagnosis, and combine multiple image processing methods, characteristics optimization selection methods and machine learning modeling methods together to explore a more simple and easy method for rice nitrogen nutrition diagnosis.

Key words: rice, image processing, characteristics extraction and optimization, computer vision technology, machine learning, nitrogen nutrition diagnosis