An improved lane detection algorithm and the definition of the error rate standard

In this paper, we propose a method to improve the problem that the assistant lane marks caused by pulse. We also define a method to distinguish the assistant lane marks' error rate objectively. To improve the problem, we mainly use the Sobel edge detection to replace the Canny edge detection. Also, we make use of the Gaussian filter to filter noise. Finally, we improve the ellipse ROI size in tracking part and the performance of the FPS (frame per second) from 32 to 39. In the past, we distinguished the assistant lane marks' error rate very subjectively. To avoid judging subjectively, we propose an objective method to define the assistant lane marks' error rate as a standard. We use the performance and the error rate to choose the ellipse ROI parameter.

[1]  Jianfeng Wang,et al.  Lane detection based on random hough transform on region of interesting , 2010, The 2010 IEEE International Conference on Information and Automation.

[2]  Chieh-Li Chen,et al.  Vision-based lane departure detection system in urban traffic scenes , 2010, 2010 11th International Conference on Control Automation Robotics & Vision.

[3]  Li-Chen Fu,et al.  A Portable Vision-Based Real-Time Lane Departure Warning System: Day and Night , 2009, IEEE Transactions on Vehicular Technology.

[4]  Suhong Ko,et al.  Lane departure identification on highway with searching the region of interest on hough space , 2007, 2007 International Conference on Control, Automation and Systems.

[5]  Wang Rong-ben,et al.  Based on Digital Image Lane Edge Detection and Tracking under Structure Environment for Autonomous Vehicle , 2007, 2007 IEEE International Conference on Automation and Logistics.

[6]  Jianmin Duan,et al.  Automatic detection technique of preceding lane and vehicle , 2008, 2008 IEEE International Conference on Automation and Logistics.

[7]  Youngjoon Han,et al.  Real-Time Lane Departure Detection Based on Extended Edge-Linking Algorithm , 2010, 2010 Second International Conference on Computer Research and Development.

[8]  Cheng-Jian Lin,et al.  Design of a lane detection and departure warning system using functional-link-based neuro-fuzzy networks , 2010, International Conference on Fuzzy Systems.

[9]  Seonyoung Lee,et al.  Implementation of lane detection system using optimized hough transform circuit , 2010, 2010 IEEE Asia Pacific Conference on Circuits and Systems.