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      • Department of Electrical and Electronics Engineering
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      Extraction of target features using infrared intensity signals

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      Author
      Aytaç, Tayfun
      Barshan, Billur
      Date
      2005-09
      Source Title
      13th European Signal Processing Conference, EUSIPCO 2005
      Publisher
      IEEE
      Pages
      169 - 172
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      We propose the use of angular intensity signals obtained with low-cost infrared (IR) sensors and present an algorithm to simultaneously extract the geometry and surface properties of commonly encountered features or targets in indoor environments. The method is verified experimentally with planes, 90° corners, and 90° edges covered with aluminum, white cloth, and Styrofoam packaging material. An average correct classification rate of 80% of both geometry and surface over all target types is achieved and targets are localized within absolute range and azimuth errors of 1.5 cm and 1.1°, respectively. Taken separately, the geometry and surface type of targets can be correctly classified with rates of 99% and 81%, respectively, which shows that the geometrical properties of the targets are more distinctive than their surface properties, and surface determination is the limiting factor. The method demonstrated shows that simple IR sensors, when coupled with appropriate signal processing, can be used to extract substantially more information than such devices are commonly employed for.
      Keywords
      Angular intensity
      Azimuth error
      Classification rates
      Geometrical property
      Indoor environment
      Infrared intensity
      Infrared sensor
      IR sensor
      Styrofoam packaging
      Surface determination
      Target feature
      Target type
      Packaging materials
      Signal processing
      Surface properties
      Geometry
      Permalink
      http://hdl.handle.net/11693/27350
      Published Version (Please cite this version)
      https://ieeexplore.ieee.org/document/7077910
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      • Department of Electrical and Electronics Engineering 3524
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