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  • 标题:Urban Road Materials Identification using Narrow Near Infrared Vision System
  • 其他标题:Urban Road Materials Identification using Narrow Near Infrared Vision System
  • 本地全文:下载
  • 作者:Heru Purnomo Ipung ; Handayani Tjandrasa
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2017
  • 卷号:7
  • 期号:3
  • 页码:1171-1179
  • DOI:10.11591/ijece.v7i3.pp1171-1179
  • 语种:English
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要: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 to identify concretes, aggregates/sands/rocks, clay, natural dry fibers and bitumen/asphalt that make up most of urban road materials. This paper proposes imaging indexes evaluation from experiment results to identify those urban road materials. There were seven narrow band optical filter sets with the center spectrum at 710nm, 730nm, 750nm, 800nm, 870nm, 905nm and 970nm. Normalization band used was 720nm using high pass optical filter. The proposed multi-spectral imaging indexes were able to show the potential to classify the selected urban road materials, another approach may need to clearly distinguish between concrete and aggregates. The comparison to the previous imaging indexes (NDVI, NDGR, NDBR) were presented that used for urban road materials identification.
  • 其他摘要: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 to identify concretes, aggregates/sands/rocks, clay, natural dry fibers and bitumen/asphalt that make up most of urban road materials. This paper proposes imaging indexes evaluation from experiment results to identify those urban road materials. There were seven narrow band optical filter sets with the center spectrum at 710nm, 730nm, 750nm, 800nm, 870nm, 905nm and 970nm. Normalization band used was 720nm using high pass optical filter. The proposed multi-spectral imaging indexes were able to show the potential to classify the selected urban road materials, another approach may need to clearly distinguish between concrete and aggregates. The comparison to the previous imaging indexes (NDVI, NDGR, NDBR) were presented that used for urban road materials identification.
  • 关键词:Computer Vision; Multispectral Image Processing;imaging index;narrow band optical filter;NDBR;NDGR;NDVI;near infrared vision system;urban road materials
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