• DocumentCode
    1500925
  • Title

    LANA: a lane extraction algorithm that uses frequency domain features

  • Author

    Kreucher, Chris ; Lakshmanan, Sridhar

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Michigan Univ., Dearborn, MI, USA
  • Volume
    15
  • Issue
    2
  • fYear
    1999
  • fDate
    4/1/1999 12:00:00 AM
  • Firstpage
    343
  • Lastpage
    350
  • Abstract
    This paper introduces a new algorithm, called lane-finding in another domain (LANA), for detecting lane markers in images acquired from a forward-looking vehicle-mounted camera. The method is based on a novel set of frequency domain features that capture relevant information concerning the strength and orientation of spatial edges. The frequency domain features are combined with a deformable template prior, in order to detect the lane markers of interest. Experimental results that illustrate the performance of this algorithm on images with varying lighting and environmental conditions, shadowing, lane occlusion(s), solid and dashed lines, etc. are presented. LANA detects lane markers well under a very large and varied collection of roadway images. A comparison is drawn between this frequency feature-based LANA algorithm and the spatial feature-based LOIS lane detection algorithm. This comparison is made from experimental, computational and methodological standpoints
  • Keywords
    Bayes methods; computer vision; computerised navigation; discrete cosine transforms; estimation theory; feature extraction; frequency-domain analysis; object recognition; road vehicles; Bayesian estimation; LANA; computer vision; discrete cosine transform; feature extraction; frequency domain analysis; global shape model; image recognition; intelligent vehicle; lane extraction algorithm; lane marker detection; lane-finding; Cameras; Computer vision; Detection algorithms; Frequency domain analysis; Image edge detection; Intelligent vehicles; Roads; Shadow mapping; Shape; Vehicle detection;
  • fLanguage
    English
  • Journal_Title
    Robotics and Automation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1042-296X
  • Type

    jour

  • DOI
    10.1109/70.760356
  • Filename
    760356