Vision-based systems for finding road lanes have to operate robustly under a wide variety of environmental conditions including large amount of scene clutters. This paper presents a method to find the lane boundaries by combining a local line extraction method and dynamic programming. The line extractor obtains an initial position of road lane boundaries from the noisy edge fragments. Then, dynamic programming improves the initial approximation to an accurate configuration of lane boundaries. Input image frame is divided into sub-regions along the vertical direction. The local line extractor extracts candidate lines of road lanes in the sub-region. Most prominent lines are found among candidate lines by dynamic programming that minimizes the functional which measures the deviation from a virtual straight line. The search framework based on DP method reduces computational cost. Experimental results using images of real road scenes demonstrate the feasibility of the proposed algorithm.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Road lane segmentation using dynamic programming for active safety vehicles


    Contributors:

    Published in:

    Pattern Recognition Letters ; 24 , 16 ; 3177-3185


    Publication date :

    2003


    Size :

    9 Seiten, 14 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Dynamic Lane Segmentation for Autonomous Vehicles Using Neural Networks

    Megalingam, Rajesh Kannan / Rudravaram, Gaurav / Kumar, Devisetty Vijay et al. | IEEE | 2022


    ACTIVE SAFETY FOR FUTURE ROAD VEHICLES

    Micke, S. | British Library Conference Proceedings | 2005



    Implementation of Road Safety Perception in Autonomous Vehicles in a Lane Change Scenario

    Del Re, Enrico / Olaverri-Monreal, Cristina | ArXiv | 2022

    Free access

    Dynamic road lane management study

    Wang, Chen | Online Contents | 2016