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Image Threshold Computation by Modelizing Knowledge/Unknowledge by Means of Atanassov’s Intuitionistic Fuzzy Sets

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Book cover Fuzzy Sets and Their Extensions: Representation, Aggregation and Models

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 220))

Abstract

In this chapter, a new thresholding technique using Atanassov’s intuitionistic fuzzy sets (A-IFSs) and restricted dissimilarity functions is introduced. We interpret the intuitionistic fuzzy index of Atanassov as the degree of unknowledge/ignorance of an expert for determining whether a pixel of an image belongs to the background or the object of the image. Under these conditions we construct an algorithm on the basis of A-IFSs for detecting the threshold of an image. Then we present a method for selecting from a set of thresholds of an image the best one. This method is based on the concept of fuzzy similarity. Lastly, we prove that in most cases our algorithm for selecting the best threshold takes the threshold calculated with the algorithm constructed on the basis of A-IFSs.

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Authors
  1. Humberto Bustince
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  2. Miguel Pagola
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  3. Pedro Melo-Pinto
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  4. Edurne Barrenechea
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  5. Pedro Couto
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Editor information

Editors and Affiliations

  1. Department of Automatics and Computation, Universidad Pública de Navarra, Campus Arrosadia s/n, 31006 Pamplona, Spain

    Humberto Bustince

  2. Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada, Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain

    Francisco Herrera

  3. Faculty of Mathematics, Universidad Complutense, Plaza de las Ciencias 3, 28040 Madrid, Spain

    Javier Montero

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Bustince, H., Pagola, M., Melo-Pinto, P., Barrenechea, E., Couto, P. (2008). Image Threshold Computation by Modelizing Knowledge/Unknowledge by Means of Atanassov’s Intuitionistic Fuzzy Sets. In: Bustince, H., Herrera, F., Montero, J. (eds) Fuzzy Sets and Their Extensions: Representation, Aggregation and Models. Studies in Fuzziness and Soft Computing, vol 220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73723-0_32

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  • DOI: https://doi.org/10.1007/978-3-540-73723-0_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73722-3

  • Online ISBN: 978-3-540-73723-0

  • eBook Packages: EngineeringEngineering (R0)

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