Title :
Detection of Corn Plant Population and Row Spacing Using Computer Vision
Author :
Wang Chuanyu ; Guo Xinyu ; Zhao Chunjiang
Author_Institution :
China Nat. Eng. Res. Center for Inf. Technol. in Agric. (NERCITA), Beijing, China
Abstract :
In this paper we present a new vision-based method to measure corn plant spacing and population at early growth stage. Images were acquired from a top-mounted camera under daylight condition. Algorithms were developed to mosaic image sequence, vegetation segmentation, image thinning, stem center identification, row Line fitting, plant count and plant spacing measurement. Compared the results of vision-based system with manual stand counts in 3 varieties with 10 repetitions of 10 m sections of corn rows. Our system was well correlated to manual stand count, and corn plant spacing estimation had no significant difference with manual stand measurements.
Keywords :
cameras; computer vision; crops; estimation theory; image segmentation; image sequences; image thinning; object detection; vegetation mapping; computer vision; corn plant population detection; corn plant row spacing detection; corn plant spacing estimation; daylight condition; image thinning; manual stand counts; manual stand measurements; mosaic image sequence; plant count; plant spacing measurement; row line fitting; stem center identification; top-mounted camera; vegetation segmentation; vision-based method; vision-based system; Agriculture; Image color analysis; Image segmentation; Lighting; Machine vision; Plants (biology); Transforms; Computer vision; Image sequence; Plant population; Plant spacing; Precision agriculture;
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2011 Second International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-1-4577-0755-1
Electronic_ISBN :
978-0-7695-4455-7
DOI :
10.1109/ICDMA.2011.106
