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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 software architecture of the vision computing modules on the DSP-core.
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f12-sensors-12-02373: The software architecture of the vision computing modules on the DSP-core.

Mentions: The experiments in this study implemented these vision computing modules on a DSP-core to guarantee the computational efficiency of the optimized video processing instruction libraries provided by TI. To set the vision computing modules as a set of executive computation entities on the DSP-core, these vision modules are realized as the “customized codecs” according to the TI CodecGengine standard [38]. Thus, these modules can serve as the computational entities and are efficiently executed on the DSP-core based on the DVSDK software architecture [37]. Therefore, these vision computing modules can be effectively run on the DSP-core (Figure 12). The main system software executed on the ARM-core (Figure 13) can also efficiently apply and control these modules to obtain the processing results of the traffic conditions in front of the host car.


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 software architecture of the vision computing modules on the DSP-core.
© Copyright Policy
Related In: Results  -  Collection

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

f12-sensors-12-02373: The software architecture of the vision computing modules on the DSP-core.
Mentions: The experiments in this study implemented these vision computing modules on a DSP-core to guarantee the computational efficiency of the optimized video processing instruction libraries provided by TI. To set the vision computing modules as a set of executive computation entities on the DSP-core, these vision modules are realized as the “customized codecs” according to the TI CodecGengine standard [38]. Thus, these modules can serve as the computational entities and are efficiently executed on the DSP-core based on the DVSDK software architecture [37]. Therefore, these vision computing modules can be effectively run on the DSP-core (Figure 12). The main system software executed on the ARM-core (Figure 13) can also efficiently apply and control these modules to obtain the processing results of the traffic conditions in front of the host car.

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.