Vision-Based Lane Detection and Tracking Algorithm

This book is about a research work on Lane Detection and Tracking Using B-snake for Autonomous Guided Vehicle. The reviews on the existing lane detection techniques are presented. A novel B-snake based lane model which describes the perspective effect of parallel lines is constructed with dual external forces for generic lane boundary or marking, it is able to describe a wider range of lane structures than other lane models such as straight and parabolic models. A robust algorithm called Canny/Hough Estimation of Vanishing Points is presented for providing a good initial position for the B-snake lane model. This algorithm is robust to noises, shadows, and illumination variations in the captured road images, and is also applicable to both the marked and the unmarked, dash paint line and solid paint line roads. A minimum energy method called MMSE (Minimum Mean Square Error) is presented to determine the parameters of road model iteratively. Road tracking is carried on after successful lane detection, by a simple external force field and MMSE method, tracking is efficient and results are good.

Autorentext

Yue Wang received his Bachelor Degree from WuHan University, Master Degree and Ph.D from Nanyang Technological University, Singapore. He has published many papers in scientific journals and conference proceedings. His research interests include pattern recognition,object segmentation and matching,video content analysis and snake model.