Title :
Crop growth estimation system using machine vision
Author :
KATAOKA, Takashi ; KANEKO, Toshihiro ; OKAMOTO, Hiroshi ; HATA, Shun-ichi
Author_Institution :
Graduate Sch. of Agric., Hokkaido Univ., Sapporo, Japan
Abstract :
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.
Keywords :
computer vision; crops; estimation theory; farming; image processing; principal component analysis; regression analysis; vegetation mapping; Gompertz curve; crop cultivation tasks; crop growing status; crop growth estimation system; crop images; exponential function; growth curve; image processing technique; machine vision; precision farming; regression analysis; vegetation mapping; Agriculture; Area measurement; Crops; Equations; Image processing; Lenses; Machine vision; Sugar industry; Testing; Vegetation mapping;
Conference_Titel :
Advanced Intelligent Mechatronics, 2003. AIM 2003. Proceedings. 2003 IEEE/ASME International Conference on
Print_ISBN :
0-7803-7759-1
DOI :
10.1109/AIM.2003.1225492