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Proceedings Paper

Computer-vision-based weed identification of images acquired by 3CCD camera
Author(s): Yun Zhang; Yong He; Hui Fang
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Paper Abstract

Selective application of herbicide to weeds at an earlier stage in crop growth is an important aspect of site-specific management of field crops. For approaches more adaptive in developing the on-line weed detecting application, more researchers involves in studies on image processing techniques for intensive computation and feature extraction tasks to identify the weeds from the other crops and soil background. This paper investigated the potentiality of applying the digital images acquired by the MegaPlusTM MS3100 3-CCD camera to segment the background soil from the plants in question and further recognize weeds from the crops using the Matlab script language. The image of the near-infrared waveband (center 800 nm; width 65 nm) was selected principally for segmenting soil and identifying the cottons from the thistles was achieved based on their respective relative area (pixel amount) in the whole image. The results show adequate recognition that the pixel proportion of soil, cotton leaves and thistle leaves were 78.24%(-0.20% deviation), 16.66% (+ 2.71% SD) and 4.68% (-4.19% SD). However, problems still exists by separating and allocating single plants for their clustering in the images. The information in the images acquired via the other two channels, i.e., the green and the red bands, need to be extracted to help the crop/weed discrimination. More optical specimens should be acquired for calibration and validation to establish the weed-detection model that could be effectively applied in fields.

Paper Details

Date Published: 27 October 2006
PDF: 7 pages
Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 60471I (27 October 2006); doi: 10.1117/12.710881
Show Author Affiliations
Yun Zhang, Zhejiang Univ. (China)
Yong He, Zhejiang Univ. (China)
Hui Fang, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 6047:
Fourth International Conference on Photonics and Imaging in Biology and Medicine
Kexin Xu; Qingming Luo; Da Xing; Alexander V. Priezzhev; Valery V. Tuchin, Editor(s)

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