Mining images to find general forms of biological objects

Authors:
Petra Perner;Horst Perner;Angela Bühring;Silke Jänichen
Affiliations:
IBaI, Institute of Computer Vision and applied Computer Sciences, Leipzig;IBaI, Institute of Computer Vision and applied Computer Sciences, Leipzig;IBaI, Institute of Computer Vision and applied Computer Sciences, Leipzig;IBaI, Institute of Computer Vision and applied Computer Sciences, Leipzig
Venue:
ICDM'04 Proceedings of the 4th international conference on Advances in Data Mining: applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications
Year:
2004

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Abstract

We propose and evaluate a method for the recognition of airborne fungi spores. We suggest a case-based object-recognition method to identify spores in a digital microscopic image. We do not use the gray values of the case, but the object edges instead. The similarity measure measures the average angle between the vectors of the template and the object. Case generation is done semi-automatically by manually tracing the object, automatic shape alignment, similarity calculation, clustering, and prototype calculation.