Visual tracking for the recovery of multiple interacting plant root systems from X-ray $$upmu $$CT images |
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Authors: | Stefan Mairhofer James Johnson Craig J. Sturrock Malcolm J. Bennett Sacha J. Mooney Tony P. Pridmore |
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Affiliation: | 1.School of Computer Science,University of Nottingham,Nottingham,UK;2.School of Biosciences,University of Nottingham,Loughborough,UK;3.Centre for Plant Integrative Biology,University of Nottingham,Loughborough,UK |
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Abstract: | We propose a visual object tracking framework for the extraction of multiple interacting plant root systems from three-dimensional X-ray micro computed tomography images of plants grown in soil. Our method is based on a level set framework guided by a greyscale intensity distribution model to identify object boundaries in image cross-sections. Root objects are followed through the data volume, while updating the tracker’s appearance models to adapt to changing intensity values. In the presence of multiple root systems, multiple trackers can be used, but need to distinguish target objects from one another in order to correctly associate roots with their originating plants. Since root objects are expected to exhibit similar greyscale intensity distributions, shape information is used to constrain the evolving level set interfaces in order to lock trackers to their correct targets. The proposed method is tested on root systems of wheat plants grown in soil. |
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