Extraction of target features using infrared intensity signals
dc.citation.epage | 172 | en_US |
dc.citation.spage | 169 | en_US |
dc.contributor.author | Aytaç, Tayfun | en_US |
dc.contributor.author | Barshan, Billur | en_US |
dc.coverage.spatial | Antalya, Turkey | |
dc.date.accessioned | 2016-02-08T11:51:11Z | |
dc.date.available | 2016-02-08T11:51:11Z | |
dc.date.issued | 2005-09 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description | Date of Conference: 4-8 Sept. 2005 | |
dc.description | Conference name: 13th European Signal Processing Conference, 2005 | |
dc.description.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. | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/27350 | |
dc.language.iso | English | en_US |
dc.publisher | IEEE | |
dc.relation.isversionof | https://ieeexplore.ieee.org/document/7077910 | |
dc.source.title | 13th European Signal Processing Conference, EUSIPCO 2005 | en_US |
dc.subject | Angular intensity | en_US |
dc.subject | Azimuth error | en_US |
dc.subject | Classification rates | en_US |
dc.subject | Geometrical property | en_US |
dc.subject | Indoor environment | en_US |
dc.subject | Infrared intensity | en_US |
dc.subject | Infrared sensor | en_US |
dc.subject | IR sensor | en_US |
dc.subject | Styrofoam packaging | en_US |
dc.subject | Surface determination | en_US |
dc.subject | Target feature | en_US |
dc.subject | Target type | en_US |
dc.subject | Packaging materials | en_US |
dc.subject | Signal processing | en_US |
dc.subject | Surface properties | en_US |
dc.subject | Geometry | en_US |
dc.title | Extraction of target features using infrared intensity signals | en_US |
dc.type | Conference Paper | en_US |
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