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An Adaptive Non Local Spatial Fuzzy Image Segmentation Algorithm

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Intelligent Computing Technology (ICIC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7389))

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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.

This work is supported by the National Natural Science Foundation of China (Grant Nos. 60970067 and 61102095), Scientific Research Program Funded by Shaanxi Provincial Education Department (No. 11JK1008), Research Fund Program of Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China (No. IPIU012011008).

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Author information

Authors and Affiliations

  1. School of Computer Science, Shaanxi Normal University, Xi’an, P.R. China

    Hanqiang Liu

  2. School of Telecommunications and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an, P.R. China

    Feng Zhao

Authors
  1. Hanqiang Liu
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  2. Feng Zhao
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Machine Learning and Systems Biology Laboratory, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    Changjun Jiang

  3. Electrical and Electronics Department, Polytechnic of Bari, Via Orabona, 4, 70125, Bari, Italy

    Vitoantonio Bevilacqua

  4. Faculty of Engineering, District University Francisco José de Caldas, Cra. 7a No. 40-53, Fifth Floor, Bogotá, Colombia

    Juan Carlos Figueroa

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© 2012 Springer-Verlag Berlin Heidelberg

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Liu, H., Zhao, F. (2012). An Adaptive Non Local Spatial Fuzzy Image Segmentation Algorithm. In: Huang, DS., Jiang, C., Bevilacqua, V., Figueroa, J.C. (eds) Intelligent Computing Technology. ICIC 2012. Lecture Notes in Computer Science, vol 7389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31588-6_48

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  • DOI: https://doi.org/10.1007/978-3-642-31588-6_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31587-9

  • Online ISBN: 978-3-642-31588-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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