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Presentation Time: 2:15 PM

QUANTIFYING THE COMPLEXITY OF BIOLOGICAL SHAPE


MIO, Washington1, LI, Mao1, MANDER, Luke2 and PUNYASENA, Surangi W.3, (1)Department of Mathematics, Florida State University, 1017 Academic Way, Tallahassee, FL 32306-4510, (2)Department of Plant Biology, University of Illinois at Urbana-Champaign, 505 S. Goodwin Avenue, Urbana, IL 61801, (3)Department of Plant Biology, University of Illinois, 505 S. Goodwin Ave., Urbana, IL 61801, mio@math.fsu.edu

We develop computational methods for quantifying the complexity of shapes that exhibit a high level of morphological variability and apply the techniques to the analysis of the patterning of the granules on the exterior wall of pollen grains. We employ these techniques in conjunction with methods of image processing and pattern analysis to develop an algorithmic approach to the taxonomic classification of several species of grasses based on morphological and textural characteristics observed in high-resolution images of pollen grains acquired through scanning electron microscopy.

Session No. 201

T146. The Future of Quantitative Paleontology: Biometry, Computer Vision, and Machine Learning
Tuesday, 6 November 2012: 1:30 PM-5:30 PM
217A (Charlotte Convention Center)
Geological Society of America Abstracts with Programs. Vol. 44, No. 7, p.479
© Copyright 2012 The Geological Society of America (GSA), all rights reserved. Permission is hereby granted to the author(s) of this abstract to reproduce and distribute it freely, for noncommercial purposes. Permission is hereby granted to any individual scientist to download a single copy of this electronic file and reproduce up to 20 paper copies for noncommercial purposes advancing science and education, including classroom use, providing all reproductions include the complete content shown here, including the author information. All other forms of reproduction and/or transmittal are prohibited without written permission from GSA Copyright Permissions.
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