Title :
Nondestructive Measurement of Tomato Seedlings during Their Growth Based on Machine Vision
Author :
Sun, Ming ; Si, Jibo ; An, Dong ; Wei, Yaoguang
Author_Institution :
Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing
Abstract :
As one of the most important technologies for plant growth modelling, the research of nondestructive measurement based on machine vision is of great significance in hastening development of digital agriculture. In this paper, we have given the example applied to nondestructive measurement of tomato seedlings during their growth in greenhouse. The leaf areas of tomato seedlings are obtained nondestructively by the nondestructive detection image capturing and image processing algorithm proposed. By analyzing the results between the machine vision based measurements and manual measurements, the best correlation coefficient of leaf areas is 0.9822, which shows that the algorithm can be used in nondestructive measurement of the tomato seedlings.
Keywords :
area measurement; computer vision; correlation methods; crops; statistical analysis; digital agriculture; greenhouse growth; image processing algorithm; leaf area correlation coefficient; machine vision; nondestructive detection image capturing algorithm; nondestructive measurement; plant growth modelling; tomato seedling growth; Agriculture; Area measurement; Biomedical monitoring; Calibration; Computer aided analysis; Crops; Image processing; Machine vision; Pixel; Plants (biology);
Conference_Titel :
Plant Growth Modeling and Applications, 2006. PMA '06. Second International Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-2851-9
DOI :
10.1109/PMA.2006.34
