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Journal of Electronic Imaging

Modular method of detection, localization, and counting of multiple-taxon pollen apertures using bag-of-words
Author(s): Gildardo Lozano-Vega; Yannick Benezeth; Franck Marzani; Frank Boochs
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Paper Abstract

Accurate recognition of airborne pollen taxa is crucial for understanding and treating allergic diseases which affect an important proportion of the world population. Modern computer vision techniques enable the detection of discriminant characteristics. Apertures are among the important characteristics which have not been adequately explored until now. A flexible method of detection, localization, and counting of apertures of different pollen taxa with varying appearances is proposed. Aperture description is based on primitive images following the bag-of-words strategy. A confidence map is estimated based on the classification of sampled regions. The method is designed to be extended modularly to new aperture types employing the same algorithm by building individual classifiers. The method was evaluated on the top five allergenic pollen taxa in Germany, and its robustness to unseen particles was verified.

Paper Details

Date Published: 27 October 2014
PDF: 10 pages
J. Electron. Imaging. 23(5) 053025 doi: 10.1117/1.JEI.23.5.053025
Published in: Journal of Electronic Imaging Volume 23, Issue 5
Show Author Affiliations
Gildardo Lozano-Vega, i3mainz (Germany)
Le2i - Lab d'Electronique, Informatique et Image (France)
Yannick Benezeth, Le2i - Lab d'Electronique, Informatique et Image (France)
Franck Marzani, Le2i - Lab d'Electronique, Informatique et Image (France)
Frank Boochs, i3mainz (Germany)


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