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

TY - JOUR

T1 - Automated classification of starch granules using supervised pattern recognition of morphological properties

AU - Wilson, Julie

AU - Hardy, Karen

AU - Allen, Richard

AU - Copeland, Les

AU - Wrangham, Richard

AU - Collins, Matthew

PY - 2010/3

Y1 - 2010/3

N2 - 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.

AB - 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.

KW - Classification

KW - Image analysis

KW - Starch morphology

KW - Supervised learning

UR - http://www.scopus.com/inward/record.url?scp=72649096966&partnerID=8YFLogxK

U2 - 10.1016/j.jas.2009.10.024

DO - 10.1016/j.jas.2009.10.024

M3 - Journal article

AN - SCOPUS:72649096966

SN - 0305-4403

VL - 37

SP - 594

EP - 604

JO - Journal of Archaeological Science

JF - Journal of Archaeological Science

IS - 3

ER -