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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.


The spatial clustering process of the bright components of interest.
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f6-sensors-12-02373: The spatial clustering process of the bright components of interest.

Mentions: In this study, Td, Tp, and Th represent the predetermined thresholds to determine the pairing characteristics of vehicle lights. These values are reasonably chosen as 3.0, 0.8, and 0.7, respectively. Figure 6 illustrates the processing results of the spatial clustering module applied to bright components. The spatial clustering process yields several groups of bright components, denoted as candidate vehicle-light groups.


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)

The spatial clustering process of the bright components of interest.
© Copyright Policy
Related In: Results  -  Collection

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

f6-sensors-12-02373: The spatial clustering process of the bright components of interest.
Mentions: In this study, Td, Tp, and Th represent the predetermined thresholds to determine the pairing characteristics of vehicle lights. These values are reasonably chosen as 3.0, 0.8, and 0.7, respectively. Figure 6 illustrates the processing results of the spatial clustering module applied to bright components. The spatial clustering process yields several groups of bright components, denoted as candidate vehicle-light groups.

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.