Real-time implementation of vision-based lane detection and tracking
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This paper presents a real-time implementation on lane detection and tracking system in order to localize lane boundaries and estimate a linear-parabolic lane model. It is realized using TMS320DM642 DSP board. Video frame is first captured with CCD camera and stored in video port buffer. Next, input image is split into sky and road region with horizon localization. Lane analysis is applied on the road region to remove road pixels. Only lane markings are the interests for the lane detection process. Once lane boundaries are located, the possible edge pixels are scanned to continuously obtain the lane model. Linear-parabolic model is used to construct the geometry of the lane. The model parameters are updated with Kalman filtering. Video sequences are tested to verify the performance of the system and it has good performance. © 2009 IEEE.
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Lim, King Hann; Seng, Kah Phooi; Ang, Li-Minn (2012)A novel lane detection technique using adaptive line segment and river flow method is proposed in this paper to estimate driving lane edges. A Kalman filtering-based B-spline tracking model is also presented to quickly ...
Lim, Hann; Seng, K.; Ang, L.; Chin, S. (2009)This chapter presents a vision-based lane-vehicle detection and tracking system comprising of (i) enhanced lane boundary detection, (ii) linear-parabolic lane region tracking, and (iii) vehicle detection with a proposed ...
Lim, Hann; Seng, K.; Ang, L.; Chin, S. (2009)This paper presents a lane detection and linear-parabolic lane tracking system using kalman filtering method. First, the image horizon is detected in a traffic scene to split the sky and road region. Road region is further ...