• DocumentCode
    677364
  • Title

    A new sky recognition with using location of sky subimage

  • Author

    Yu-Kumg Chen ; Tsung-Hsien Tsai

  • Author_Institution
    Dept. of Electron. Eng., Huafan Univ., New Taipei, Taiwan
  • fYear
    2013
  • fDate
    26-28 Aug. 2013
  • Firstpage
    1103
  • Lastpage
    1108
  • Abstract
    When a car drives through underpass, tunnel, or under the viaduct, etc., GPS will not be able to receive the satellite signals and makes the error navigation. In order to resolve this problem, a new sky recognition technique for driving-view image from the video of VEDR is proposed in this paper. With finding the distant center of road for driving-view image, the location of sky subimage is corrected in the first step of the proposed algorithm. Based on the theory of entropy, the road conditions of T-junction, skewed road, and shaded trees are determined in the sky subimage of driving-view image. Then, with analysis and statistics of gray scale image from the sky subimage of driving-view image, the road conditions of tunnel, underpass, and viaduct are separated from the road conditions of sky. Experimental results are carried out with some varied conditions of driving-view images, and show our proposed algorithm succeed in recognition of these road conditions.
  • Keywords
    data recording; driver information systems; entropy; image recognition; statistical analysis; video signal processing; T-junction road condition; VEDR video; driving-view image; entropy theory; gray scale image analysis; gray scale image statistics; shaded trees; skewed road condition; sky recognition technique; sky subimage location; tunnel; underpass; vehicle event data recorder; viaduct; Entropy; Global Positioning System; Image color analysis; Image edge detection; Roads; Satellites; Driving-view image; GPS; Sky recognition; Sky subimage; VEDR;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2013 IEEE International Conference on
  • Conference_Location
    Yinchuan
  • Type

    conf

  • DOI
    10.1109/ICInfA.2013.6720460
  • Filename
    6720460