Abstract
In this paper we give an overview of both classical and more modern morphological techniques. We will demonstrate their utility through a range of practical examples. After discussing the fundamental morphological ideas, we show how the classic morphological opening and closing filters lead to measures of size via granulometries, and we will discuss briefly their implementation. We also present an overview of morphological segmentation techniques, and the use of connected openings and thinnings will be demonstrated. This then leads us into the more recent set-theoretic notions of graph based approaches to image analysis.
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Breen, E.J., Jones, R. & Talbot, H. Mathematical morphology: A useful set of tools for image analysis. Statistics and Computing 10, 105–120 (2000). https://doi.org/10.1023/A:1008990208911
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DOI: https://doi.org/10.1023/A:1008990208911