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Using imaging brightness information to select feature bands for multi-spectral images of cabbage leaves
Author(s): Pengfei Cao; Weiye Yang; Jie Feng; Weiping Yang
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Paper Abstract

The experiment takes cabbage leaves as research object to capture images based on multi-spectral imaging system with combination of LCTF and CMOS camera by every 5 nm interval from 400 nm to 720 nm. Firstly, according to the principle of image brightness information, the value of distinguish degree for cabbage leaves are calculated with every band; Then through sorting the value of distinguish degree for cabbage leaves, along with information features of the image and distinguish degree, it can be concluded that band 555 nm, 715 nm, 710 nm, 575 nm, 535 nm, 520 nm, 720 nm, 605 nm and 650 nm have better distinguish degree; Finally, the classification accuracy statistic of feature bands for cabbage leaves is 95.56% and 93.13% through using the principle of Euclidean distance and spectral angle match respectively. It can draw a conclusion that the selected bands are with ideal classification accuracy for cabbage leaves. Therefore, 555 nm, 715 nm, 710 nm, 575 nm, 535 nm, 520nm, 720 nm, 605 nm and 650 nm can be used as feature bands for cabbage leaves. To select feature bands for cabbage leaves is one of effective means to identify the status for plants, which provides a method for fine classification and data processing for plant multi-spectral images with broad prospects and ideal application value.

Paper Details

Date Published: 24 October 2017
PDF: 7 pages
Proc. SPIE 10461, AOPC 2017: Optical Spectroscopy and Imaging, 104610D (24 October 2017); doi: 10.1117/12.2282091
Show Author Affiliations
Pengfei Cao, Longdong Univ. (China)
Weiye Yang, Zunyi Medical Univ. (China)
Jie Feng, Yunnan Normal Univ. (China)
Weiping Yang, Yunnan Normal Univ. (China)


Published in SPIE Proceedings Vol. 10461:
AOPC 2017: Optical Spectroscopy and Imaging
Jin Yu; Zhe Wang; Wei Hang; Bing Zhao; Xiandeng Hou; Mengxia Xie; Tsutomu Shimura, Editor(s)

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