2017
DOI: 10.11591/ijece.v7i3.pp1171-1179
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Urban Road Materials Identification using Narrow Near Infrared Vision System

Abstract: An urban road materials vision system using narrow band near infrared imaging indexes were proposed. This proposed imaging indexes were enhancement for previous work on autonomous multispectral road sensing method. Each urban road material has different near infrared spectral patterns which is as the base of its spectral identification. The new proposed imaging indexes, which using similar formula of NDVI, was normalized with narrow band near infrared spectrum range of 720nm to 1000nm of wavelength, were used … Show more

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Cited by 3 publications
(3 citation statements)
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“…According to the traffic carrying capacity and traditional traffic volume forecast, Nancheng New District has designed the basic scheme of the interchange. Among them, in order to adapt to the right-turn traffic volume, the right-turn ramp in the new district adopts a directional or semidirectional ramp [ 18 ]. Others turn less traffic and therefore use roundabouts.…”
Section: Urban Interchange Under the Integration Of Smart Transportat...mentioning
confidence: 99%
“…According to the traffic carrying capacity and traditional traffic volume forecast, Nancheng New District has designed the basic scheme of the interchange. Among them, in order to adapt to the right-turn traffic volume, the right-turn ramp in the new district adopts a directional or semidirectional ramp [ 18 ]. Others turn less traffic and therefore use roundabouts.…”
Section: Urban Interchange Under the Integration Of Smart Transportat...mentioning
confidence: 99%
“…Metode pengembangan citra NIR (Near Infrared) pita sempit untuk identifikasi material telah diujicobakan (Ipung, 2017). Dengan cara yang sama, ujicoba dilakukan untuk kandungan air didalam pasir dengan mengunakan kamera yang relatif terjangkau.…”
Section: Studi Pustakaunclassified
“…Recognizing materials is important for interacting, understanding, and summarizing complex and novel scenes. Material recognition plays a fundamental role in numerous applications including robotic grasping and pushing [38,10,46], path navigation for au-tonomous vehicles [8,23], quantification of surface albedo for climate modeling [39], land-use assessment [28], road network recognition [6], and crop coverage and agricultural assessment [18]. Material segmentation for satellite imagery is particularly of interest for applications such as road segmentation [19,3], land cover albedo analysis [35], and tree-cover for fire risk assessment [17].…”
Section: Introductionmentioning
confidence: 99%