• DocumentCode
    179438
  • Title

    Automatic initialization for naval application of graph segmentation techniques: A comparative study

  • Author

    Camino, Irene ; Zolzer, Udo

  • Author_Institution
    Helmut Schmidt Univ. Hamburg, Hamburg, Germany
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    5120
  • Lastpage
    5124
  • Abstract
    Nowadays, many different image processing applications are of high interest to maritime authorities because of security reasons. Depending on the application, different kinds of images are employed. The extraction of ship silhouettes requires high resolution images in order to obtain accurate results. However, when the characteristics of the naval environment are visible the background complexity increases greatly and automatic approaches fail. In order to overcome these difficulties we propose an automatic initialization for graph segmentation techniques. A comparative study of earlier suggested initializations for different graph segmentation techniques is also presented. It shows that, under such unfavorable image conditions, finding the proper initialization in an automatic way is not trivial. Yet, the precision and recall achieved by our initialization are considerable higher regardless the graph segmentation. Furthermore, the performance is highly increased since the best results are obtained after only the first iteration.
  • Keywords
    feature extraction; image resolution; image segmentation; iterative methods; ships; automatic initialization; background complexity; graph segmentation; high resolution images; image processing; iterative segmentation; naval image; ship silhouette extraction; Conferences; Image color analysis; Image resolution; Image segmentation; Marine vehicles; Shape; Three-dimensional displays; automatic initialization; graph segmentation; naval images; silhouette extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6854578
  • Filename
    6854578