Fuzzy Local Binary Patterns for Ultrasound Texture Characterization

  • Dimitris K. Iakovidis
  • Eystratios G. Keramidas
  • Dimitris Maroulis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5112)


B-scan ultrasound provides a non-invasive low-cost imaging solution to primary care diagnostics. The inherent speckle noise in the images produced by this technique introduces uncertainty in the representation of their textural characteristics. To cope with the uncertainty, we propose a novel fuzzy feature extraction method to encode local texture. The proposed method extends the Local Binary Pattern (LBP) approach by incorporating fuzzy logic in the representation of local patterns of texture in ultrasound images. Fuzzification allows a Fuzzy Local Binary Pattern (FLBP) to contribute to more than a single bin in the distribution of the LBP values used as a feature vector. The proposed FLBP approach was experimentally evaluated for supervised classification of nodular and normal samples from thyroid ultrasound images. The results validate its effectiveness over LBP and other common feature extraction methods.


Fuzzy Local Binary Patterns Ultrasound Thyroid nodules Support Vector Machines 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Dimitris K. Iakovidis
    • 1
  • Eystratios G. Keramidas
    • 1
  • Dimitris Maroulis
    • 1
  1. 1.Dept. of Informatics and TelecommunicationsUniversity of AthensAthensGreece

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