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Medical Edge Detection Combining Fuzzy Mathematical Morphology with Interval-Valued Relations

  • Agustina Bouchet
  • Pelayo Quirós
  • Pedro Alonso
  • Irene DíazEmail author
  • Susana Montes
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 368)

Abstract

Image processing represents an important challenge in different fields, especially in biomedical field. Mathematical Morphology uses concepts from set theory, geometry, algebra and topology to analyze the geometrical structure of an image. In addition, it is possible to consider methods where the starting point to analyze an image is a fuzzy relation. This paper studies three methods to image edge detection based on a construction method for interval-valued fuzzy relations which can be understood as a gradient from a morphological point of view. The performance of the proposal in detecting medical image edges is tested, showing the method performing better with regard to a least squared adjust.

Keywords

Interval-valued fuzzy sets Fuzzy sets Fuzzy mathematical morphology Gradient Edge detection 

Notes

Acknowledgments

This work has been partially supported by MEC and FEDER Grant TEC2012-38142-C04-04 and by ERASMUS Mundus Project EUREKA SD 2013-2591.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Agustina Bouchet
    • 1
    • 5
  • Pelayo Quirós
    • 2
  • Pedro Alonso
    • 2
  • Irene Díaz
    • 3
    Email author
  • Susana Montes
    • 4
  1. 1.Engineering Faculty, Digital Image Processing GroupNational University of Mar del PlataMar del PlataArgentina
  2. 2.Department of MathematicsUniversity of OviedoGij ónSpain
  3. 3.Department of Computer ScienceUniversity of OviedoOviedoSpain
  4. 4.Department of Statistics and O. R.University of OviedoGij ónSpain
  5. 5.CONICETMar del PlataArgentina

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