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Proceedings Paper

Research on crop and weed identification by NIR spectroscopy
Author(s): Jiazhi Pan; Yueming Tang; Yong He
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Paper Abstract

Crop and weed identification is very importance in precision farming field. As spectroscopy can reflects the contents of object tested, so it is possible to identify crop and weed with high correct rate. ASD FieldSpec recorded the spectrum of crops and weeds. Its waveband is 325-1075nm and with resolution of 3.5nm. One crop seedling and three kinds of weeds living together were tested. Each species has at least 30 sampling spectrum taken down. As one sample spectrum has too much data, wavelet transform reduced the data volume firstly, which compressed source signals to tens of floating numbers from 751 floating numbers. Totally 160 samples were used to build a radial basis function neural network, the object output was a 4 by 1 dimension vector. Those left 43 samples used to check the identifying capability. As neural network model has huge power in solving these pattern recognition problems. It can approach to giving finite function at any approximation. Nearly all these predicting samples classified right. Therefore, by using spectroscopy in the identification is possible, and having high correct rate. Further more, the computation is very fast. Whereas the spectrometer is expensive and easily affected by shaking and variation of light shine, it cannot installed directly on vehicles at present time. In the future, it may be possible to recognize crop and weed in real time by using spectroscopy.

Paper Details

Date Published: 29 January 2007
PDF: 7 pages
Proc. SPIE 6279, 27th International Congress on High-Speed Photography and Photonics, 62797D (29 January 2007); doi: 10.1117/12.725951
Show Author Affiliations
Jiazhi Pan, Zhejiang Univ. (China)
Yueming Tang, Zhejiang Univ. (China)
Yong He, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 6279:
27th International Congress on High-Speed Photography and Photonics
Xun Hou; Wei Zhao; Baoli Yao, Editor(s)

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