Scanning Microscopy


Image segmentation by mathematical morphology is a methodology based upon the notions of watershed and homotopy modification.This paper aims at introducing this methodology through various examples of segmentation in materials sciences, electron microscopy and scene analysis.

First, we defined our basic tool, the watershed transform. We showed that this transformation can be built by implementing a flooding process on a greytone image. This flooding process can be performed by using elementary morphological operations such as geodesic skeleton and reconstruction. Other algorithms are also briefly presented (arrows representation).

Then, the use of this transformation for image segmentation purposes is discussed. The application of the watershed transform to gradient images and the problems raised by over-segmentation are emphasized. This leads, into the third part, to the introduction of a general methodology for segmentation, based on the definition of markers and on a transformation called homotopy modification. This complex tool is defined in detail and various types of implementations are given.

Many examples of segmentation are presented. These examples are taken from various fields: transmission electron microscopy, scanning electron microscopy (SEM), 3D holographic pictures, radiography, non destructive control and so on.

The final part of this paper is devoted to the use of the watershed transformation for hierarchical segmentation. This tool is particularly efficient for defining different levels of segmentation starting from a graph representation of the images based on the mosaic image transform. This approach will be explained by means of examples in industrial vision and scene analysis.

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