• Title/Summary/Keyword: Vehicle Break-lamp

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Implementation of Preceding Vehicle Break-Lamp Detection System using Selective Attention Model and YOLO (선택적 주의집중 모델과 YOLO를 이용한 선행 차량 정지등 검출 시스템 구현)

  • Lee, Woo-Beom
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.2
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    • pp.85-90
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    • 2021
  • A ADAS(Advanced Driver Assistance System) for the safe driving is an important area in autonumous car. Specially, a ADAS software using an image sensors attached in previous car is low in building cost, and utilizes for various purpose. A algorithm for detecting the break-lamp from the tail-lamp of preceding vehicle is proposed in this paper. This method can perceive the driving condition of preceding vehicle. Proposed method uses the YOLO techinicque that has a excellent performance in object tracing from real scene, and extracts the intensity variable region of break-lamp from HSV image of detected vehicle ROI(Region Of Interest). After detecting the candidate region of break-lamp, each isolated region is labeled. The break-lamp region is detected finally by using the proposed selective-attention model that percieves the shape-similarity of labeled candidate region. In order to evaluate the performance of the preceding vehicle break-lamp detection system implemented in this paper, we applied our system to the various driving images. As a results, implemented system showed successful results.