Automated classification of starch granules using supervised pattern recognition of morphological properties
Research output: Contribution to journal › Journal article › Research › peer-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 language | English |
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Journal | Journal of Archaeological Science |
Volume | 37 |
Issue number | 3 |
Pages (from-to) | 594-604 |
Number of pages | 11 |
ISSN | 0305-4403 |
DOIs | |
Publication status | Published - 2010 |
Externally published | Yes |
- Classification, Image analysis, Starch morphology, Supervised learning
Research areas
ID: 229396596