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Fuzzy Connectedness Segmentation: A Brief Presentation of the Literature

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Combinatorial Image Analysis (IWCIA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9448))

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Abstract

For any positive integer M, M-object fuzzy connectedness (FC) segmentation is a methodology for finding M objects in a digital image based on user-specified seed points and user-specified functions, called (fuzzy) affinities, which map each pair of image points to a value in the real interval [0, 1]. FC segmentation has been used with considerable success on biomedical and other images. We provide a brief presentation of the literature on the topic of FC segmentation.

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Author information

Authors and Affiliations

  1. Computer Science PhD Program, The Graduate Center, City University of New York, 365 Fifth Avenue, New York, NY, 10016, USA

    Gabor T. Herman & T. Yung Kong

  2. Computer Science Department, Queens College, City University of New York, 65-30 Kissena Boulevard, Flushing, NY, 11367, USA

    T. Yung Kong

  3. Department of Mathematics, West Virginia University, Morgantown, WV, 26506, USA

    Krzysztof Chris Ciesielski

Authors
  1. Gabor T. Herman
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  2. T. Yung Kong
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  3. Krzysztof Chris Ciesielski
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Corresponding author

Correspondence to Gabor T. Herman .

Editor information

Editors and Affiliations

  1. SUNY Fredonia, Fredonia, New York, USA

    Reneta P. Barneva

  2. Advanced Computing and Microelectronics, Indian Statistical Institute, Kolkata, Germany

    Bhargab B. Bhattacharya

  3. SUNY Buffalo State, Buffalo, New York, USA

    Valentin E. Brimkov

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Herman, G.T., Kong, T.Y., Ciesielski, K.C. (2015). Fuzzy Connectedness Segmentation: A Brief Presentation of the Literature. In: Barneva, R., Bhattacharya, B., Brimkov, V. (eds) Combinatorial Image Analysis. IWCIA 2015. Lecture Notes in Computer Science(), vol 9448. Springer, Cham. https://doi.org/10.1007/978-3-319-26145-4_2

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  • DOI: https://doi.org/10.1007/978-3-319-26145-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26144-7

  • Online ISBN: 978-3-319-26145-4

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