Experiment of Multispectral Sensing Sensor for Urban Road Materials in Outdoor Environment

Matthew Rio Darmawan; Heru Purnomo Ipung; Maulahikmah Galinium

doi:10.33555/iconiet.v2i3.32

Matthew Rio Darmawan Swiss German University
Heru Purnomo Ipung Swiss German University
Maulahikmah Galinium Swiss German University

DOI: https://doi.org/10.33555/iconiet.v2i3.32

Keywords: Multispectral, Urban road materials, Imaging index

Abstract

This research is the first attempt to conduct several experiments of multispectral
sensing sensor for urban road materials in outdoor environment. This research aims to classify
five urban road materials that are aggregates, asphalts, concrete, clay, natural fibre including
vegetation and water. There were 9 cameras in the multispectral sensing sensor. Seven camera
attached with narrow band optical filter with the centre spectrum at 710nm, 730nm, 750nm,
800nm, 870nm, 905nm and 950nm. One camera attached with 720 nm normalization band uses
high pass optical filter. Another camera attached with UV/IR cut optical filter works as a RGB
camera. The images results, that have been taken, are processed in MATLAB to get the imaging
index results from the multispectral system. Naïve Bayes classifier is used in Weka to classify
the urban road materials with vegetation and water. The first classification and testing that
classifies five urban road materials with vegetation and water have accuracy results ranged from
0 % to 32% while the accuracy results without vegetation and water have better accuracy results
ranged from 0 % to 55 %.