IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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Vehicle Detection for Adaptive Head-Lamp Control of Night Vision System

적응형 헤드 램프 컨트롤을 위한 야간 차량 인식

  • 김현구 (영남대학교 정보통신학과) ;
  • 정호열 (영남대학교 정보통신학과) ;
  • 박주현 (영남대학교 전기공학과)
  • Received : 2010.09.24
  • Accepted : 2010.12.08
  • Published : 2011.02.28
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Abstract

This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, in order to effectively extract spotlight of interest, a pre-signal-processing process based on camera lens filter and labeling method is applied on road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process use light tracking method and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with visible light mono-camera and tested it in urban and rural roads. Through the test, classification performances are above 89% of precision rate and 94% of recall rate evaluated on real-time environment.

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References

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