Distance Transformations Based on Ordered Weighted Averaging Operators

Lopez-Molina, Carlos
De Miguel, Laura
Iglesias-Rey, Sara
Bustince, Humberto
De Baets, Bernard
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Binary image comparison has been a study subject for a long time, often rendering in context-specific solutions that depend upon the type of visual contents in the binary images. Distance transformations have been a recurrent tool in many of such solutions. The literature contains works on the generation and definition of distance transformations, but also on how to make a sensible use of their results. In this work, we attempt to solve one of the most critical problems in the application of distance transformations to real problems: their oversensitivity to certain spurious pixels which, even if having a minimal visual impact in the binary images to be compared, may have a severe impact on their distance transforms. With this aim, we combine distance transformations with Ordered Weighted Averaging (OWA) operators, a well-known information fusion tool from Fuzzy Set Theory.
Soft Computing: Theory Innovations and Problem Solving Benefits, binary image comparison, boundary image comparison, distance transformations, owa operator
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