首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Automated classification of starch granules using supervised pattern recognition of morphological properties
Authors:Julie Wilson  Karen Hardy  Richard Allen  Les Copeland  Richard Wrangham  Matthew Collins
Institution:1. Departments of Chemistry and Mathematics, University of York, York YO10 5YW, United Kingdom;2. ICREA at Universidad Autónoma de Barcelona, Bellaterra 08193, Spain;3. University of York, York YO10 5YW, United Kingdom;4. Faculty of Agriculture, Food and Natural Resources, University of Sydney, Australia;5. Department of Anthropology, Harvard University, 11 Divinity Avenue, Cambridge, MA 01238, USA;1. Research Laboratory for Archaeology and the History of Art, University of Oxford, Dyson Perrins Building, Oxford OX1 3QY, United Kingdom;2. School of Social Science, Michie Building, The University of Queensland, St. Lucia 4072, Australia;3. Department of Archaeology, 2500 University Drive, NW., Calgary T2N 1N4, Alberta, Canada;1. Birbal Sahni Institute of Palaeobotany, 53, University Road, Lucknow 226 007, India;2. CSIR- National Institute of Oceanography, Dona Paula, Goa 403 004, India;1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China;2. The Foundation for Archaeobotanical Research in Microfossils, PO Box 37, Fairfax, VA 22038, USA;3. Department of Geography and Geoinformation Science, Center for Earth Observing and Space Research, George Mason University, Fairfax, VA 22030, USA;1. School of Archaeology and Ancient History, University of Leicester, Leicester, United Kingdom;2. Archaeology and Geosciences, Australian Museum, Sydney NSW, Australia
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.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号