• DocumentCode
    74273
  • Title

    Adaptive shadow detection using global texture and sampling deduction

  • Author

    Ke Jiang ; Ai-hua Li ; Zhi-gao Cui ; Tao Wang ; Yan-zhao Su

  • Author_Institution
    502 Fac., Xi´an Inst. of High Technol., Xi´an, China
  • Volume
    7
  • Issue
    2
  • fYear
    2013
  • fDate
    Apr-13
  • Firstpage
    115
  • Lastpage
    122
  • Abstract
    An adaptive shadow detection algorithm is proposed to eliminate interference on object detection from the shadow. The algorithm uses three components in YUV colour space to identify shadow pixels from the candidate foreground. An adaptive threshold estimator is designed to improve shadow detection accuracy and adaptive capacity in various lighting conditions. This estimator uses edge detection method to obtain global texture, as well statistical calculations to obtain the thresholds. Algorithm has the characteristic of low complexity and little restraint; hence it is suitable for real time-moving shadow detection in various lighting conditions. Experiment results show that this algorithm can obtain a high detection accuracy and the time-assume is greatly shortened compared with other algorithms with similar accuracy.
  • Keywords
    edge detection; image colour analysis; image matching; image sampling; image texture; interference suppression; lighting; object detection; real-time systems; statistical analysis; YUV colour space; adaptive capacity; adaptive shadow detection algorithm; adaptive threshold estimator; edge detection method; global texture; high detection accuracy; interference elimination; lighting conditions; object detection; real time-moving shadow detection; sampling deduction; statistical calculations;
  • fLanguage
    English
  • Journal_Title
    Computer Vision, IET
  • Publisher
    iet
  • ISSN
    1751-9632
  • Type

    jour

  • DOI
    10.1049/iet-cvi.2012.0106
  • Filename
    6519167