Automated classification of starch granules using supervised pattern recognition of morphological properties

Julie Wilson, Karen Hardy, Richard Allen, Les Copeland, Richard Wrangham, Matthew Collins

Research output: Contribution to journalArticleResearchpeer-review

31 Citations (Scopus)

Abstract

Image analysis techniques have been used to investigate the likelihood of being able to classify and assign a probability regarding the plant origin of individual starch granules in a collection of granules. Quantifiable variables were used to characterize the granules, and the assignments and probabilities were calculated objectively. We consider the classification of images containing granules of a single species and of mixed species and the possibility of assigning a class to granules of unknown species in an image of a slide obtained from the dental calculus of chimpanzees. © 2009 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)594-604
JournalJournal of Archaeological Science
Volume37
Issue number3
DOIs
Publication statusPublished - 1 Jan 2010

Keywords

  • Classification
  • Image analysis
  • Starch morphology
  • Supervised learning

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