Title :
Cellular multi-core fusion-tracking system
Author :
Rekeczky, C. ; Kozek, T.
Author_Institution :
Eutecus, Inc., Berkeley, CA, USA
Abstract :
A novel real-time signal processing device has been designed and implemented for improved target feature extraction, discrimination, and tracking. The device utilizes a unique combination of advanced signal processing techniques for multi-spectral fusion and image analysis. It incorporates state-of-the-art algorithm and the associated electronics to combine the functions of a multi-spectral fusion (MSF) engine and a multi-target tracking and discrimination (MTTD) engine. The resulting compact MSF-MTTD system, currently is capable of processing image flows from two external sensors (e.g. infrared and visible) by utilizing the processing power of massively parallel cellular nonlinear processor architectures at different levels of processing. Within this framework topographic data fusion (Stage 1) is followed by parallel feature extraction (Stage 2) and the analysis, tracking and discrimination (Stage 3) of multiple targets at ultra-high frame rates (>1000 fps). The compact (<2in??3) light-weight (<25 g), low-power (<5 W for the entire system) prototype of the multi-core MSF-MTTD engine and system has been implemented on high-end FPGAs and will be described in this paper.
Keywords :
feature extraction; field programmable gate arrays; image fusion; MSF-MTTD engine; cellular multicore fusion-tracking system; parallel cellular nonlinear processor architectures; parallel feature extraction; real-time signal processing device; target feature extraction; topographic data fusion; Engines; Feature extraction; Field programmable gate arrays; Image analysis; Infrared image sensors; Prototypes; Sensor systems; Signal design; Signal processing algorithms; Target tracking;
Conference_Titel :
Cellular Nanoscale Networks and Their Applications (CNNA), 2010 12th International Workshop on
Conference_Location :
Berkeley, CA
Print_ISBN :
978-1-4244-6679-5
DOI :
10.1109/CNNA.2010.5430283