Preliminary research on total nitrogen content prediction of sandalwood using the error-in-variable models based on digital image processing.

ABSTRACT: This paper presents a method for predicting the total nitrogen content in sandalwood using digital image processing. The goal of this study is to provide a real-time, efficient, and highly automated nutritional diagnosis system for producers by analyzing images obtained in forests. Using images acquired from field servers, which were installed in six forest farms of different cities located in northern Hainan Province, we propose a new segmentation algorithm and define a new indicator named "growth status" (GS), which includes two varieties: GSMER (the ratio of sandalwood pixels to the minimum enclosing rectangle pixels) and GSMCC (the ratio of sandalwood pixels to minimum circumscribed circle pixels). We used the error-in-variable model by considering the errors that exist in independent

SUBMITTER: Chen Z 

PROVIDER: S-EPMC6103514 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature