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Image-based search and retrieval for biface artefacts using features capturing archaeologically significant

Mark Eramian1, Ekta Walia1, Christopher Power2

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Archaeologists can now search digital artifact photos more effectively using an image-based retrieval system. This system helps identify similar biface artifacts, improving archaeological research and discovery.

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Area of Science:

  • Archaeology
  • Computer Science
  • Digital Humanities

Background:

  • Digitized photographs are crucial for archaeological recording and artifact analysis.
  • Current image retrieval methods are hindered by sparse or inconsistent metadata, impeding efficient searching.
  • Keyword-based searches are often insufficient for exploring large archaeological image collections.

Purpose of the Study:

  • To develop and evaluate an image-based retrieval system for biface artifacts.
  • To address the challenge of finding specific images within large archaeological digital collections.
  • To improve the efficiency and accuracy of archaeological image search.

Main Methods:

  • Conducted a contextual inquiry study with biface experts to identify key artifact characteristics.
  • Devised and implemented several image descriptors for matching biface images.
  • Evaluated descriptor performance using specific measures comparing returned image sets.

Main Results:

  • The study identified key characteristics for image-based artifact retrieval.
  • Different image descriptors showed varying strengths and weaknesses in performance.
  • The developed system offers a more effective alternative to keyword-based searches.

Conclusions:

  • Image-based retrieval systems can significantly enhance the searchability of archaeological image collections.
  • Understanding expert criteria is vital for designing effective image feature descriptors.
  • This research provides valuable insights for developing improved digital search systems in archaeology.