Distance Measures between Digital Fuzzy Objects and Their Applicability in Image Processing

Abstract

We present two different extensions of the Sum of minimal distances and the Complement weighted sum of minimal distances to distances between fuzzy sets. We evaluate to what extent the proposed distances show monotonic behavior with respect to increasing translation and rotation of digital objects, in noise free, as well as in noisy conditions. Tests show that one of the extension approaches leads to distances exhibiting very good performance. Furthermore, we evaluate distance based classification of crisp and fuzzy representations of objects at a range of resolutions. We conclude that the proposed distances are able to utilize the additional information available in a fuzzy representation, thereby leading to improved performance of related image processing tasks.

Keywords

Fuzzy sets; set distance; registration; classification

Published in

Lecture Notes in Computer Science
2011, volume: 6636, pages: 385-397
Title: Combinatorial Image Analysis
Publisher: Springer-Verlag

Conference

14th International Workshop on Combinatorial Image Analysis (IWCIA)

SLU Authors

• Lindblad, Joakim

  • Centre for Image Analysis, Swedish University of Agricultural Sciences
    
  • Serbian Academy of Sciences and Arts

• Sladoje, Nataša

  • University of Novi Sad

UKÄ Subject classification

Computer Science

Publication identifier

• DOI: https://doi.org/10.1007/978-3-642-21073-0_34
• ISBN: 978-3-642-21072-3

Permanent link to this page (URI)

https://res.slu.se/id/publ/35982