Open AccessDevelopment of online classification system for construction waste based on industrial camera and hyperspectral camera
Author(s) -
Wen Xiao,
Jianhong Yang,
Huaiying Fang,
Jiangteng Zhuang,
Yuedong Ku
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0208706
Subject(s) - hyperspectral imaging , particle swarm optimization , artificial intelligence , linear discriminant analysis , computer science , extreme learning machine , digital camera , discriminant , spectral imaging , computer vision , pattern recognition (psychology) , machine learning , remote sensing , geography , artificial neural network
Construction waste is a serious problem that should be addressed to protect environment and save resources, some of which have a high recovery value. To efficiently recover construction waste, an online classification system is developed using an industrial near-infrared hyperspectral camera. This system uses the industrial camera to capture a region of interest and a hyperspectral camera to obtain the spectral information about objects corresponding to the region of interest. The spectral information is then used to build classification models based on extreme learning machine and resemblance discriminant analysis. To further improve this system, an online particle swarm optimization extreme learning machine is developed. The results indicate that if a near-infrared hyperspectral camera is used in conjunction with an industrial camera, construction waste can be efficiently classified. Therefore, extreme learning machine and resemblance discriminant analysis can be used to classify construction waste. Particle swarm optimization can be used to further enhance the proposed system.