Fuzzy-Marker-Based Segmentation Using Hierarchies
Authors: 
Gabriel Barbosa da Fonseca, Benjamin Perret, Romain Negrel, Jean Cousty, Silvio Jamil F. GuimarãesAuthors Info & Claims
Pages 391 - 403
Abstract
This article extends a classical marker-based image segmentation method proposed by Salembier and Garrido in 2000. In the original approach, the segmentation relies on two sets of pixels which play the role of object and background markers. In the proposed extension, the markers are not represented by crisp sets, but by fuzzy ones, i.e., functions of the image domain into the real interval [0, 1] indicating the degree of membership of each pixel to the markers. We show that when the fuzzy markers are indicator functions of crisp sets, the proposed method produces the same result as the original one. We present a linear-time algorithm for computing the result of the proposed method given two fuzzy markers and we establish the correctness of this algorithm. Additionally, we discuss possible applications of the proposed approach, such as adjusting marker strength in interactive image segmentation procedures and optimizing marker locations with gradient descent methods.
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Information
Published In
May 2021
552 pages
ISBN:978-3-030-76656-6
DOI:10.1007/978-3-030-76657-3
- Editors:
- Joakim Lindblad,
- Filip Malmberg,
- Nataša Sladoje
© Springer Nature Switzerland AG 2021.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 24 May 2021
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