Region growing structuring elements and new operators based on their shape

REGSE figure


Vincent Morard, Etienne Decencière, Petr Dokladal
Centre de Morphologie Mathématique
Mathématiques et Systèmes, MINES ParisTech;
35, rue Saint-Honoré, 77305 Fontainebleau CEDEX - France

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This paper proposes new adaptive structuring elements in the framework of mathematical morphology. These structuring elements (SEs) have a fixed size but they adapt their shape to the image content by choosing, recursively, similar pixels in gray-scale, with regard to the seed pixel. These new SEs are called region growing structuring elements (REGSEs). Then, we introduce an original method to obtain some features by analyzing the shape of each REGSE. We get a powerful set of operators, which is able to enhance efficiently thin structures in an image. We illustrate the performance of the proposed filters with an application: the detection of cracks in the framework of non-destructive testing. We compare these methods with others, including morphological amoebas and general adaptive neighborhood structuring elements and we see that these operators, based on REGSE, yield the best detection for our application.

Paper (preprint)

paper REGSE

Conference information and copyrights

The 13th IASTED International Conference on Signal and Image Processing (SIP), December, 2011. Dallas, USA.