Locally adaptable mathematical morphology using distance transformations

Authors:
Olivier Cuisenaire
Affiliations:
Signal Processing Institute (ITS), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland
Venue:
Pattern Recognition
Year:
2006

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Abstract

We investigate how common binary mathematical morphology operators can be adapted so that the size of the structuring element can vary across the image pixels. We show that when the structuring elements are balls of a metric, locally adaptable erosion and dilation can be efficiently implemented as a variant of distance transformation algorithms. Opening and closing are obtained by a local threshold of a distance transformation, followed by the adaptable dilation.