Paper
24 October 2017 Using imaging brightness information to select feature bands for multi-spectral images of cabbage leaves
Pengfei Cao, Weiye Yang, Jie Feng, Weiping Yang
Author Affiliations +
Proceedings Volume 10461, AOPC 2017: Optical Spectroscopy and Imaging; 104610D (2017) https://doi.org/10.1117/12.2282091
Event: Applied Optics and Photonics China (AOPC2017), 2017, Beijing, China
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pengfei Cao, Weiye Yang, Jie Feng, and Weiping Yang "Using imaging brightness information to select feature bands for multi-spectral images of cabbage leaves", Proc. SPIE 10461, AOPC 2017: Optical Spectroscopy and Imaging, 104610D (24 October 2017); https://doi.org/10.1117/12.2282091
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KEYWORDS
Imaging systems

Multispectral imaging

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