1. 国家农业信息化工程技术研究中心, 北京 100097 2. 中国农业大学理学院, 北京 100193 3. University of Hohenheim, 700599 Stuttgart, Germany
Study on Spectral Detection of Green Plant Target
DENG Wei1, ZHAO Chun-jiang1*, HE Xiong-kui2, CHEN Li-ping1, ZHANG Lu-da2, WU Guang-wei1, Mueller J3, ZHAI Chang-yuan1
1. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China 2. College of Science, China Agricultural University, Beijing 100193, China 3. University of Hohenheim, 700599 Stuttgart, Germany
Abstract：Weeds grow scatteredly in fields, where many insentient objects exist, for example, withered grasses, dry twig and barriers. In order to improve the precision level of spraying, it is important to study green plant detecting technology. The present paper discussed detecting method of green plant by using spectral recognizing technology, because of the real-time feature of spectral recognition. By analyzing the reflectivity difference between each of the two sides of the “red edge” of the spectrum from plants and surrounding environment, green plant discriminat index (GPDI) is defined as the value which equals the reflectivity ratio at the wavelength of 850 nm divided by the reflectivity ratio at the wavelength of 650 nm. The original spectral data of green plants and the background were measured by using the handhold FieldSpec 3 Spectroradiometer manufactured by ASD Inc. in USA. The spectral data were processed to get the reflectivity of each measured objects and to work out the GPDI thereof as well. The classification model of green plant and its background was built up using decision tree method in order to obtain the threshold of GPDI to distinguish green plants and the background. The threshold of GPDI was chosen as 5.54. The detected object was recognized as green plant when it is GPDI>GPDITH, and vice versa. Through another test, the accuracy rate was verified which was 100% by using the threshold. The authors designed and developed the green plant detector based on single chip microcomputer (SCM) “AT89S51” and photodiode “OPT101” to realize detecting green plants from the background. After passing through two optical filters, the center wavelengths of which are 650 and 850 nm respectively, the reflected light from measured targets was detected by two photodiodes and converted into electrical signals. These analog signals were then converted to digital signals via an analog-to-digital converter (ADS7813) after being amplified by a signal amplifier (OP400). The converted digital signal of reflected light was eventually sent to the SCM (AT89S51) and was calculated and processed there. The processing results and the control signals were given out to actuate executive device to open or close the solenoid valve. The test results show that the level of detectivity of the designed detector was affected by the species, size, and density of weeds. The detectivity of broad-leaf species is higher than that of narrow-leaf species. Broad-leaf species are more easily detected than those narrow-leaf ones; the bigger the plants and the denser the leaves are, the higher the level of detectivity is.
Key words：Spectral detection;Green plant discriminant index (GPDI);Spectral red-edge characteristics
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