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

Research output: Contribution to journalJournal articleResearchpeer-review

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.

Original languageEnglish
JournalJournal of Archaeological Science
Volume37
Issue number3
Pages (from-to)594-604
Number of pages11
ISSN0305-4403
DOIs
Publication statusPublished - 2010
Externally publishedYes

    Research areas

  • Classification, Image analysis, Starch morphology, Supervised learning

ID: 229396596