A Real-Time Embedded Blind Spot Safety Assistance System

This paper presents an effective vehicle and motorcycle detection system in the blind spot area in the daytime and nighttime scenes. The proposed method identifies vehicle and motorcycle by detecting the shadow and the edge features in the daytime, and the vehicle and motorcycle could be detected through locating the headlights at nighttime. First, shadow segmentation is performed to briefly locate the position of the vehicle. Then, the vertical and horizontal edges are utilized to verify the existence of the vehicle. After that, tracking procedure is operated to track the same vehicle in the consecutive frames. Finally, the driving behavior is judged by the trajectory. Second, the lamps in the nighttime are extracted based on automatic histogram thresholding, and are verified by spatial and temporal features to against the reflection of the pavement. The proposed real-time vision-based Blind Spot Safety-Assistance System has implemented and evaluated on a TI DM6437 platform to perform the vehicle detection on real highway, expressways, and urban roadways, and works well on sunny, cloudy, and rainy conditions in daytime and night time. Experimental results demonstrate that the proposed vehicle detection approach is effective and feasible in various environments.

• Record URL:
  • http://www.hindawi.com/journals/ijvt/2012/506235/
• Authors:
  • Wu, Bing-Fei
  • Kao, Chih-Chung
  • Li, Ying-Feng
  • Tsai, Min-Yu
• Publication Date: 2012

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References;
• Pagination: 15 p
• Serial:
  • International Journal of Vehicular Technology
  • Volume: 2012
  • Publisher: Hindawi Publishing Corporation
  • Serial URL: http://www.hindawi.com/journals/ijvt/

Subject/Index Terms

• TRT Terms: Blind spots; Daylight; Image analysis; Night; Traffic safety; Vehicle detectors
• Uncontrolled Terms: Lane departures
• Geographic Terms: Taiwan
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment; I83: Accidents and the Human Factor; I90: Vehicles;

Filing Info

• Accession Number: 01370113
• Record Type: Publication
• Files: TRIS
• Created Date: May 16 2012 3:06PM