A general image based nematode identification system design

Authors:
Bai-Tao Zhou;Won Nah;Kang-Woong Lee;Joong-Hwan Baek
Affiliations:
School of Electronics and Communication Engineering, Hankuk Aviation University, Korea;School of Electronics and Communication Engineering, Hankuk Aviation University, Korea;School of Electronics and Communication Engineering, Hankuk Aviation University, Korea;School of Electronics and Communication Engineering, Hankuk Aviation University, Korea
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Year:
2005

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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.