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Image acquisition and analysis of hazardous biological material in air

: Sklarczyk, C.; Perner, H.; Rieder, H.; Arnold, W.; Perner, P.

Postprint urn:nbn:de:0011-n-1298033 (3.8 MByte PDF)
MD5 Fingerprint: f8c2a8aafa9cbdebe995a4da4f1574eb
The original publication is available at
Created on: 9.7.2010

Perner, P.:
Advances in mass data analysis of signals and images in medicine, biotechnology and chemistry : International conference, MDA 2006/2007, Leipzig, Germany, July 18, 2007; Selected papers
Berlin: Springer, 2007 (Lecture Notes in Artificial Intelligence 4826)
ISBN: 3-540-76299-X
ISBN: 978-3-540-76299-7
ISSN: 0302-9743
International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology and Chemistry (MDA) <2007, Leipzig>
Conference Paper, Electronic Publication
Fraunhofer IZFP ()
Case-based object recognition; case-based reasoning; image analysis; image interpretation; microbiological probe handling; microscopic image acquisition

Human beings are exposed every day to bio-aerosols in the various fields of their personal and/or professional daily life. The European Commission has rules 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, probe handling and image-interpretation system for airborne fungi identification. We explain the application domain and describe the development issues. The development strategy and the architecture of the system are described and some results are presented.