Summary
This chapter presents the main concepts of morphological image processing. Mathematical morphology has application in diverse areas of image processing such as filtering, segmentation and pattern recognition, applied both to binary and gray-scale images. Section 4.2 addresses the basic binary morphological operations: erosion, dilation, opening and closing. We also present applications of the primary operators, paying particular attention to morphological reconstruction because of its importance and since it is still not widely known. In Sect. 4.3, the same concepts are extended to gray-scale images. Section 4.4 is devoted to watershed-based segmentation. There are many variants of the watershed transform. We introduce the watershed principles with real-world applications. The key to successful segmentation is the design of the marker to eliminate the over-segmentation problem. Finally, Sect. 4.5 presents the multi-scale watershed to segment brain structures from diffusion tensor imaging, a relatively recent imaging modality that is based on magnetic resonance.
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Lotufo, R.A., Rittner, L., Audigier, R., Machado, R.C., Saúde, A.V. (2010). Morphological Image Processing Applied in Biomedicine. In: Deserno, T. (eds) Biomedical Image Processing. Biological and Medical Physics, Biomedical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15816-2_4
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