This paper presents a novel algorithm for nighttime detection of the lane markers painted on a road at night. First of all, the proposed algorithm uses neighborhood average filtering, 8-directional Sobel operator and thresholding segmentation based on OTSU's to handle raw lane images taken from a digital CCD camera. Secondly, combining intensity map and gradient map, we analyze the distribution features of pixels on boundaries of lanes in the nighttime and construct 4 feature sets for these points, which are helpful to supply with sufficient data related to lane boundaries to detect lane markers much more robustly. Then, the searching method in multiple directions- horizontal, vertical and diagonal directions, is conducted to eliminate the noise points on lane boundaries. Adapted Hough transformation is utilized to obtain the feature parameters related to the lane edge. The proposed algorithm can not only significantly improve detection performance for the lane marker, but it requires less computational power. Finally, the algorithm is proved to be reliable and robust in lane detection in a nighttime scenario.
S China Univ Technol, Sch Civil Engn & Transportat, Guangzhou 510640, Peoples R China;Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi 830011, Peoples R China;S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510640, Peoples R China
You Feng,Zhang Ronghui,Zhong Lingshu,et al. lane detection algorithm for night-time digital image based on distribution feature of boundaty pixels[J]. JOURNAL OF THE OPTICAL SOCIETY OF KOREA,2013,17(2):188-199.