IJMLC 2018 Vol.8(2): 144-151 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.2.678

An Automated Probe Handling and Image Inspection System for the Recognition of Biological Hazardous Material in the Air

Petra Perner

Abstract—Human beings are exposed every day to bio-aerosols in their personal and professional life. The European Commission has issued regulations for protecting employees in the workplace from biological hazards. Airborne fungi can be detected and identified by an image-acquisition and interpretation system. In this paper, we present recent results on the development of an automated image acquisition, sample handling and image-interpretation system for airborne fungi identification. We explained the application domain and described the development issues. The development strategy and the architecture of the system are described, and results are presented.

Index Terms—Health monitoring, Microscopic image acquisition, microbiological sample handling, image analysis, image interpretation, case-based object recognition, case-based reasoning.

Petra Perner is with the Institute of Computer Vision and applied Computer Sciences, PF 30 11 14, 04251 Leipzig, Germany (e-mail: pperner@ibai-institut.de).

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Cite: Petra Perner, "An Automated Probe Handling and Image Inspection System for the Recognition of Biological Hazardous Material in the Air," International Journal of Machine Learning and Computing vol. 8, no. 2, pp. 144-151, 2018.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Scopus (since 2017), Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net