Distance transformations based on ordered weighted averaging operators
Fecha
2021Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Contribución a congreso / Biltzarrerako ekarpena
Versión
Versión publicada / Argitaratu den bertsioa
Identificador del proyecto
Impacto
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nodoi-noplumx
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Resumen
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 r ...
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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. [--]
Materias
Binary image comparison,
Boundary image comparison,
Distance transformations,
OWA operator
Editor
University of Hawaii Press
Publicado en
Bui, T. X. (Ed.): Proceedings of the Hawaii International Conference on System Sciences, HICSS 2021. University of Hawaii Press, 2021, 2115 - 2124,
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Entidades Financiadoras
The authors gratefully acknowledge the
financial support of the Spanish Research
Agency, project PID2019-108392GB-I00
(AEI/10.13039/501100011033), as well as that by
Navarra de Servicios y Tecnologías (Nasertic).