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    Reflectance Transformation Imaging and ImageJ: Comparing Imaging Methodologies for Cultural Heritage Artefacts

    Electronic Visualisation and the Arts (EVA 2017)

    London, UK, 11 - 13 July 2017


    David Saunders, Richard Collmann & Ann Borda



    The imaging of cultural heritage sites and artefacts is now a highly technical process with many tools and methodological approaches available to archaeologists, architects, museum curators and artefact conservators. Imaging studies at the Australian Institute of Archaeology (AIA) have been directed principally to the recording of the artefacts within the collection. Several imaging tools have been used, including optical microscopy, pseudo 3D photography using a translation rig, flatbed scanning and Reflectance Transformation Imaging (RTI). RTI is an important tool for the on-going Cuneiform in Australian and New Zealand collections (CANZ) project, one output of which will be a web-site from which researchers will be able to load the interactive RTI files that can be viewed using Cultural Heritage Imaging (CHI) algorithmic rendering tools. Where publication of the AIA artefacts through journal articles and monographs is to be undertaken, other imaging techniques are being investigated to capture or enhance detail in a single image.

    In this work, we compare the outputs of RTI and ImageJ for interactive imaging and for single image publishing. This paper presents the results of applying ImageJ processing tools to images taken using the RTI methodology. Two types of artefact were studied in this work: (i) a clay tablet with significant relief in the incised cuneiform text and with convex surfaces and (ii) a papyrus fragment with ink script and a relatively flat surface texture. Both artefacts were imaged using the RTI illuminating dome methodology and the reflectance functions developed for algorithmic rendering. Image data for both artefacts were also processed using ImageJ enhancement tools, specifically Z-Project. The resultant images are compared with those from RTI algorithmic rendering.


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