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Abstract

We introduce the use of DC programming, in combination with convex-concave regularization, as a deterministic approach for solving the optimization problem imposed by defuzzification by feature distance minimization. We provide a DC based algorithm for finding a solution to the defuzzification problem by expressing the objective function as a difference of two convex functions and iteratively solving a family of DC programs. We compare the performance with the previously recommended method, simulated annealing, on a number of test images. Encouraging results, together with several advantages of the DC based method, approve use of this approach, and motivate its further exploration

Published in

Image And Signal Processing And Analysis
2007, pages: 373-378

Conference

5th International Symposium on Image and Signal Processing and Analysis

SLU Authors

  • Lindblad, Joakim

    • Centre for Image Analysis, Swedish University of Agricultural Sciences

UKÄ Subject classification

Computer graphics and computer vision

Publication identifier

  • DOI: https://doi.org/10.1109/ISPA.2007.4383722
  • ISBN: 978-953-184-116-0

Permanent link to this page (URI)

https://res.slu.se/id/publ/17125