• DocumentCode
    249628
  • Title

    Spatial information based FCM for infrared ship target segmentation

  • Author

    Xiangzhi Bai ; Zhiguo Chen ; Yu Zhang ; Zhaoying Liu ; Yi Lu

  • Author_Institution
    Image Process. Center, Beihang Univ., Beijing, China
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    5127
  • Lastpage
    5131
  • Abstract
    Segmentation of infrared (IR) ship images is always a challenging task, because of the intensity inhomogeneity and noise. The Fuzzy C-Means (FCM) clustering is a classical method widely used in IR ship image segmentation. However, it has some shortcomings, like not considering the spatial information or being sensitive to noise. In this paper, an improved FCM algorithm based on the spatial information is proposed. The improvements include two parts: (1) adding the non-local spatial information based on the ship target; (2) using the spatial shape information of the contour of the ship target to refine the local spatial constraint by Markov Random Field (MRF). A preprocessing procedure and a target selection method are also used to further improve the performance of the segmentation result. Experimental results show that our method is very effective and performs better than the conventional FCM methods in segmentation of the infrared ship images.
  • Keywords
    Markov processes; fuzzy set theory; image segmentation; infrared imaging; ships; FCM; IR ship image segmentation; MRF; Markov random field; fuzzy c-means clustering; infrared ship target segmentation; local spatial constraint; preprocessing procedure; spatial information; Active contours; Clustering algorithms; Image segmentation; Marine vehicles; Noise; Pattern recognition; Standards; FCM; IR ship image; Image segmentation; MRF; Spatial information;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7026038
  • Filename
    7026038