Browsing by Subject "Infrared emitters"

Now showing 1 - 2 of 2

Open Access
Position-invariant surface recognition and localization using infrared sensors
(SPIE, 2003) Barshan, B.; Aytaç, T.
Low-cost infrared emitters and detectors are used for the recognition of surfaces with different properties in a location-invariant manner. The intensity readings obtained with such devices are highly dependent on the location and properties of the surface in a way that cannot be represented in a simple manner, complicating the recognition and localization process. We propose the use of angular intensity scans and present an algorithm to process them. This approach can distinguish different surfaces independently of their positions. Once the surface is identified, its position can also be estimated. The method is verified experimentally with the surfaces aluminum, white painted wall, brown kraft paper, and polystyrene foam packaging material. A correct differentiation rate of 87% is achieved, and the surfaces are localized within absolute range and azimuth errors of 1.2 cm and 1.0 deg, respectively. The method demonstrated shows that simple infrared sensors, when coupled with appropriate processing, can be used to extract a significantly greater amount of information than they are commonly employed for. © 2003 Society of Photo-Optical Instrumentation Engineers.
Open Access
Surface differentiation and position estimation by parametric modeling of signals obtained with infrared sensors
(IEEE, 2004) Aytaç, Tayfun; Barshan, Billur
In this study, low-cost infrared emitters and detectors are used for the recognition of surfaces with different properties in a location-invariant manner. The intensity readings obtained with such sensors are highly dependent on the location and properties of the surface in a way that cannot be represented analytically in a simple manner, complicating the differentiation and localization process. Our approach, which models infrared angular intensity scans parametrically, can distinguish different surfaces independently of their positions. Once the surface type is identified, its position can also be estimated. The method is verified experimentally with wood, styrofoam packaging material, white painted wall, white and black clothes, and white, brown, and violet papers. A correct differentiation rate of 73% is achieved over eight surfaces and the surfaces are localized within absolute range and azimuth errors of 0.8 cm and 1.1°, respectively. The differentiation rate improves to 86% over seven surfaces and 100% over six surfaces. The method demonstrated shows that simple infrared sensors, when coupled with appropriate processing, can be used to extract a significantly greater amount of information than they are commonly employed for.