Abstract
In this chapter we will attempt a first image segmentation; we will try to identify image segments that represent interesting objects such as, for example, mineral grains. To discriminate the pixels that belong to the segments from those that do not belong we consider the gray values of the individual pixels without considering their neighborhoods. In other words, we use point operations (POPs). We will formulate criteria to discriminate segments based on the gray values alone, irrespective of where they occur.
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References
Web Publications
NIH Image manual http://rsb.info.nih.gov/nih-image/manual/appendices/macros.html
Software Downloads
Lazy LUTs macro http://earth.unibas.ch/micro – click on ‘software’ link
NIH Image macros http://rsb.info.nih.gov/nih-image/more-docs/macros.html
NIH Image User macros http://rsb.info.nih.gov/nih-image/download/user-macros
Publications
Barrett SD, Bickmore BR, Rufe E, Hochella MF, Torzo G, Cerolini D (1998) The use of macros in AFM image analysis and image processing. J Comp Ass Microsc 10:77–82
Bickmore BR, Rufe E, Barrett SD, Hochella MF (1999) Measuring discrete feature dimensions in atomic force microscopy images with Image SXM. Geol Mater Res 1:5–19
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© 2014 Springer-Verlag Berlin Heidelberg
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Heilbronner, R., Barrett, S. (2014). Segmentation by Point Operations. In: Image Analysis in Earth Sciences. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10343-8_5
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DOI: https://doi.org/10.1007/978-3-642-10343-8_5
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