Plant leaf nervure structure acquiring based on 3CCD image processing

Hui Fang; Wei Chen; Yong He; Xiangqing Ye

doi:10.1117/12.710667

27 October 2006 Plant leaf nervure structure acquiring based on 3CCD image processing

Hui Fang, Wei Chen, Yong He, Xiangqing Ye

Proceedings Volume 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine; 60470O (2006) https://doi.org/10.1117/12.710667
Event: Fourth International Conference on Photonics and Imaging in Biology and Medicine, 2005, Tianjin, China

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.

Citation Download Citation

Hui Fang, Wei Chen, Yong He, and Xiangqing Ye "Plant leaf nervure structure acquiring based on 3CCD image processing", Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 60470O (27 October 2006); https://doi.org/10.1117/12.710667

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