• DocumentCode
    3761657
  • Title

    Rain drop detection and removal using K-Means clustering

  • Author

    M. Ramesh Kanthan;S. Naganandini Sujatha

  • Author_Institution
    Research and Development center, Bharathiar University, Coimbatore, India
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A novel hybrid algorithm has been proposed in this paper to detect raindrops, remove and then restore the image back ground in a single image. This new hybrid algorithm is framed based on K-Means clustering and Median filtering for the fast retrieval of Rain droplets from the single image. K-Means clustering algorithm is an efficient algorithm for image clustering. The algorithm proposed in this paper has different approach from other established numerical schemes. The hybrid algorithm is framed in order to identify the rain droplets using clustering and shape modeling of raindrops. The proposed system is fast compared with alternate droplet identification schemes. The process allows rapid evaluation of the contour of the raindrops and convergence to its final resultant with very little iteration. The experiments demonstrate the efficiency and accuracy of the method.
  • Keywords
    "Rain","Clustering algorithms","Transforms","Algorithm design and analysis","Computational modeling","Lesions","Image segmentation"
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Computing Research (ICCIC), 2015 IEEE International Conference on
  • Print_ISBN
    978-1-4799-7848-9
  • Type

    conf

  • DOI
    10.1109/ICCIC.2015.7435707
  • Filename
    7435707