GrainAutLine: an Environment for Semi-Automatic Processing of Marble Thin Section Images

Authors

  • Kristóf Csorba
    Affiliation

    Department of Automation and Applied Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Hungary

  • Ádám Budai
    Affiliation

    Department of Automation and Applied Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Hungary

  • Judit Zöldföldi
    Affiliation

    Institute of Material Science, University of Stuttgart, Stuttgart, Germany

  • Balázs Székely
    Affiliation

    Department of Geophysics and Space Sciences, Eötvös Loránd University, Budapest, Hungary

https://doi.org/10.3311/PPee.10890

Abstract

GrainAutLine is an interdisciplinary microscopy image analysis tool with domain specific smart functions to partially automate the processing of marble thin section images. It allows the user to create a clean grain boundary image which is a starting point of several archaeometric and geologic analyses. The semi-automatic tools minimize the need for carefully drawing the grain boundaries manually, even in cases where twin crystals prohibit the use of classic edge detection based boundary detection. Due to the semi-automatic approach, the user has full control over the process and can modify the automatic results before finalizing a specific step. This approach guarantees high quality results both in cases where the process is easy to automate, and also if it needs more help from the user. This paper presents the basic operation of the system and details about the provided tools as a case study for an interdisciplinary, semi-automatic image processing application.

Keywords:

marble, thin section, grain boundary, semi-automatic segmentation, software tool

Citation data from Crossref and Scopus

Published Online

2017-08-17

How to Cite

Csorba, K., Budai, Ádám, Zöldföldi, J., Székely, B. “GrainAutLine: an Environment for Semi-Automatic Processing of Marble Thin Section Images”, Periodica Polytechnica Electrical Engineering and Computer Science, 61(4), pp. 305–311, 2017. https://doi.org/10.3311/PPee.10890

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Articles