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Proceedings Paper

Plant leaf nervure structure acquiring based on 3CCD image processing
Author(s): Hui Fang; Wei Chen; Yong He; Xiangqing Ye
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Paper Abstract

This research work is part of research of plant image based modeling, which is a main research area in virtual plant. To modeling the plant, the first step is to make model for leafs. And to modeling leafs, the first step is to acquire its nervure structure. So, this thesis dissertate a plant leaf nervure structure acquiring system base on MS3100 3CCD image processing. By the 3CCD image system, three channel data (green, red and near-infrared) images were gotten. The image data were transferred to a host computer and were stored as files in TIFF format. With further image processing, we can get a relatively more clear vision of plant nervure image. By means of non-contact measuring method, main geometrical characteristic parameters of plant nervure can be acquired in image or grid format. This process includes the technologies such as imaging pre-processing, image binary-conversion, boundary encoding and so on. The second part is to establish the vector structure of the leaf nervure. The establishment of tree structure of the plant leaf nervure is mainly discussed. At last plant leaf nervure in vector format based on the multi-spectrum images gotten from 3CCD camera can be acquired.

Paper Details

Date Published: 27 October 2006
PDF: 7 pages
Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 60470O (27 October 2006); doi: 10.1117/12.710667
Show Author Affiliations
Hui Fang, Zhejiang Univ. (China)
Wei Chen, Zhejiang Univ. (China)
Yong He, Zhejiang Univ. (China)
Xiangqing Ye, Xuhu Agricultural Dept. (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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