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A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

Chen YL, Chiang HH, Chiang CY, Liu CM, Yuan SM, Wang JH - Sensors (Basel) (2012)

Bottom Line: The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle.These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform.Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei 10608, Taiwan. ylchen@csie.ntut.edu.tw

ABSTRACT
This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

No MeSH data available.


Results of vehicle detection and event determination for a nighttime rural road under a dim illumination with free-flowing traffic conditions (Test video 3).
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f19-sensors-12-02373: Results of vehicle detection and event determination for a nighttime rural road under a dim illumination with free-flowing traffic conditions (Test video 3).

Mentions: First, the experimental videos in Figures 17–19 (Test videos 1–3) are evaluated at nighttime rural roads under normal and dim lighting conditions with free traffic flows. The snapshots in Figures 17–19 show that the proposed system correctly detects most of the preceding and oncoming vehicles, estimates their distances to the host car, and warns the driver to avoid possible collision dangers under different illumination conditions. The system also activates the event recording process when the host car drives too close to the target vehicles ahead.


A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

Chen YL, Chiang HH, Chiang CY, Liu CM, Yuan SM, Wang JH - Sensors (Basel) (2012)

Results of vehicle detection and event determination for a nighttime rural road under a dim illumination with free-flowing traffic conditions (Test video 3).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376597&req=5

f19-sensors-12-02373: Results of vehicle detection and event determination for a nighttime rural road under a dim illumination with free-flowing traffic conditions (Test video 3).
Mentions: First, the experimental videos in Figures 17–19 (Test videos 1–3) are evaluated at nighttime rural roads under normal and dim lighting conditions with free traffic flows. The snapshots in Figures 17–19 show that the proposed system correctly detects most of the preceding and oncoming vehicles, estimates their distances to the host car, and warns the driver to avoid possible collision dangers under different illumination conditions. The system also activates the event recording process when the host car drives too close to the target vehicles ahead.

Bottom Line: The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle.These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform.Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei 10608, Taiwan. ylchen@csie.ntut.edu.tw

ABSTRACT
This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

No MeSH data available.