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An Adaptive Non Local Spatial Fuzzy Image Segmentation Algorithm

  • Hanqiang Liu
  • Feng Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7389)

Abstract

Fuzzy c-means clustering algorithm (FCM) is one of the most widely used methods for image segmentation. In order to overcome the sensitivity of FCM to noise in images, we introduce a novel non local adaptive spatial constraint term, which is defined by using the non local spatial information of pixels, into the objective function of FCM and propose an adaptive non local spatial fuzzy image segmentation algorithm (ANLS_FIS). In this method, the non-local spatial information of each pixel plays a different role in image segmentation. ANLS_FIS can effectively deal with noise while preserving the geometrical edges in the image. Experiments on synthetic and real images, especially magnetic resonance (MR) images, show that ANLS_FIS is more robust than the modified FCM algorithms with local spatial constraint.

Keywords

FCM Image segmentation Non-local spatial information adaptive spatial constraint term noisy image Magnetic resonance (MR) image 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hanqiang Liu
    • 1
  • Feng Zhao
    • 2
  1. 1.School of Computer ScienceShaanxi Normal UniversityXi’anP.R. China
  2. 2.School of Telecommunications and Information EngineeringXi’an University of Posts and TelecommunicationsXi’anP.R. China

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