Simultaneous extraction of geometry and surface properties of targets using simple infrared sensors
Date
2004Source Title
Optical Engineering
Print ISSN
0091-3286
Publisher
SPIE
Volume
43
Issue
10
Pages
2437 - 2447
Language
English
Type
ArticleItem Usage Stats
196
views
views
200
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downloads
Abstract
We investigate the use of low-cost infrared (IR) sensors for the simultaneous extraction of geometry and surface properties of commonly encountered features or targets in indoor environments, such as planes, corners, and edges. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting target in a way that cannot be represented by a simple analytical relationship, therefore complicating the localization and recognition process. We propose the use of angular intensity scans and present an algorithm to process them to determine the geometry and the surface type of the target and estimate its position. The method is verified experimentally with planes, 90-deg corners, and 90-deg 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 deg, 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 processing, can be used to extract substantially more information than that for which such devices are commonly employed. © 2004 Society of Photo-Optical Instrumentation Engineers.
Keywords
Feature extractionInfrared sensors
Optical sensing
Pattern recognition
Position estimation
Surface differentiation
Surface localization
Target differentiation
Target localization
Algorithms
Edge detection
Feature extraction
Infrared imaging
Object recognition
Optical sensors
Scanning
Surface properties
Position estimation
Surface differentiation
Surface localization
Target differentiation
Target localization
Image sensors
Permalink
http://hdl.handle.net/11693/24216Published Version (Please cite this version)
http://dx.doi.org/10.1117/1.1789136Collections
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