• DocumentCode
    12951
  • Title

    A Hierarchical Horizon Detection Algorithm

  • Author

    Shen, Yu-Fei ; Krusienski, D. ; Li, Jie ; Rahman, Zahid

  • Author_Institution
    Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA, USA
  • Volume
    10
  • Issue
    1
  • fYear
    2013
  • fDate
    Jan. 2013
  • Firstpage
    111
  • Lastpage
    114
  • Abstract
    A hierarchical elastic computer-aided detection algorithm is proposed to automatically detect the horizon in an aerial image. A hierarchical strategy, including coarse-level detection and fine-level adjustment, is applied. First, the original image is blurred by a large-scale low-pass filter. Then, a Canny edge detector and Hough transform are successively utilized to find major edges in the image and identify lines associated with those major edges. The desired horizon is modeled by the resulting line that best satisfies certain criteria. By doing so, the general position of the horizon can be quickly detected at the coarse-level step. Since the horizon is often not a straight line, an elastic fine-level adjustment is applied to capture the precise curvature of the horizon. A quantitative performance metric is designed, and preliminary experimental results show the feasibility and reliability of the proposed algorithm.
  • Keywords
    Detection algorithms; Detectors; Image edge detection; NASA; Reliability; Search methods; Transforms; Horizon detection;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2012.2194473
  • Filename
    6200304