Target Identification Using Sensors of Different Nature

Vagale, Anete; Ņikitenko, Agris; Slava, Eduards; Osen, Ottar L.

doi:10.1515/acss-2017-0015

Abstract

In the present paper, a new and improved visual sensor data fusion method is proposed that uses visible and far-infrared light sensors. Additionally, lux meter data are used for decision level fusion of beliefs of recognised target classes. The database consisting of 4 ambient light condition images is created using Canon and FLIR cameras.

The developed approach has been tested using database images, neural network training and classification, particularly for low light level conditions. Enhancements of target identification precision are proved by practical implementation and testing of the proposed method.

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Target Identification Using Sensors of Different Nature

Abstract

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