Differentiation and localization of targets using infrared sensors
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This study investigates the use of low-cost infrared emitters and detectors in the differentiation and localization of commonly encountered features or targets in indoor environments, such as planes, corners, edges, and cylinders. The intensity readings obtained with such systems are highly dependent on target location and properties in a way which cannot be represented in a simple manner, making the differentiation and localization process difficult. In this paper, we propose the use of angular intensity scans and present an algorithm to process them. This approach can determine the target type independent of its position. Once the target type is identified, its position can also be estimated. The method is verified experimentally. An average correct classification rate of 97% over all target types is achieved and targets are localized within absolute range and azimuth errors of 0.8 cm and 1.6°, 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 that which they are commonly employed for.
Pattern recognition and feature extraction