Abstract
Nematodes are primitive organisms which nonetheless devour many of the essential resources that are critical for human beings. For effective and quick inspection and quarantine, we propose a general image based system for quantitatively characterizing and identifying nematodes. We also describe the key methods ranging from gray level image acquisition and processing to information extraction for automated detection and identification. The main contributions of this paper are not only presenting a framework of the system architecture, but also giving detail analysis and implementation of each system component with instance of Caenorhabditis elegans. Therefore with a little modification, this system can be applied to other nematode species discrimination and analysis.
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© 2005 Springer-Verlag Berlin Heidelberg
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Zhou, BT., Nah, W., Lee, KW., Baek, JH. (2005). A General Image Based Nematode Identification System Design. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596981_132
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DOI: https://doi.org/10.1007/11596981_132
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30819-5
Online ISBN: 978-3-540-31598-8
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