Crop growth estimation system using machine vision

被引：277

作者：

Kataoka, T ^{[1
]}

Kaneko, T ^{[1
]}

Okamoto, H ^{[1
]}

Hata, S ^{[1
]}

机构：

[1] Hokkaido Univ, Grad Sch Agr, Sapporo, Hokkaido 0608589, Japan

来源：

PROCEEDINGS OF THE 2003 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM 2003), VOLS 1 AND 2 | 2003年

关键词：

crop status; exponential function; growth curve; map; precision farming; regression analysis; segmentation; vision system;

D O I：

10.1109/aim.2003.1225492

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

According to the philosophy of Precision Farming, the status of crops during their growing stages is important information for crop cultivation tasks and management. The system which was developed in this research involves the vegetation cover area of plant being determined by the vision system and the image processing technique, and the crop status, i.e., the plant height, the leaf length, and the dry matter being estimated with the specific functions. The specific functions which show the relationship between the vegetation cover area of plants and the measured actual plant dimensions were analyzed using a growth curve (the Gompertz curve) and an exponential function. The Gompertz curve was used for the estimation of the dry mass of the plants. For the leaf length and the plant height, the exponential function worked well compared to the growth curve. Based on the results, the crop growing status could be estimated using crop images and calculated equations.

引用

页码：1079 / 1083

页数：5