A hit-or-miss transform for multivariate images

Authors:
E. Aptoula;S. Lefèvre;C. Ronse
Affiliations:
Image Sciences, Computer Sciences and Remote Sensing Laboratory (LSIIT) UMR-7005 CNRS, University of Strasbourg, Pôle API, Blvd Sébastien Brant, P.O. Box 10413, 67412 Illkirch Cedex, Fra ...;Image Sciences, Computer Sciences and Remote Sensing Laboratory (LSIIT) UMR-7005 CNRS, University of Strasbourg, Pôle API, Blvd Sébastien Brant, P.O. Box 10413, 67412 Illkirch Cedex, Fra ...;Image Sciences, Computer Sciences and Remote Sensing Laboratory (LSIIT) UMR-7005 CNRS, University of Strasbourg, Pôle API, Blvd Sébastien Brant, P.O. Box 10413, 67412 Illkirch Cedex, Fra ...
Venue:
Pattern Recognition Letters
Year:
2009

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Abstract

The hit-or-miss transform (HMT) is considered to be among the fundamental operations in the morphological toolbox. Initially, it was defined for binary images, as a morphological approach to the problem of template matching, whereas its extension to grey-level data has been problematic, leading to multiple definitions, that have been only recently unified by means of a common theoretical foundation. In this paper, we generalise these definitions to the case of multivariate images, and propose a vectorial HMT, allowing the detection of objects over multiple image channels. Moreover, in order to counter the operator's extreme sensitivity to variations, rank order filters as well as synthetic structuring functions are studied in the context of multivariate data. We additionally present examples of the use of the suggested operator in combination with colour images.