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Modular method of detection, localization, and counting of multiple-taxon pollen apertures using bag-of-words

[+] Author Affiliations
Gildardo Lozano-Vega

i3mainz, Fachhochschule Mainz, Lucy-Hillebrand-Strasse 2, 55128 Mainz, Germany

Le2i, Université de Bourgogne, B.P. 47870, 21078 Dijon Cedex, France

Yannick Benezeth

Le2i, Université de Bourgogne, B.P. 47870, 21078 Dijon Cedex, France

Franck Marzani

Le2i, Université de Bourgogne, B.P. 47870, 21078 Dijon Cedex, France

Frank Boochs

i3mainz, Fachhochschule Mainz, Lucy-Hillebrand-Strasse 2, 55128 Mainz, Germany

J. Electron. Imaging. 23(5), 053025 (Oct 27, 2014). doi:10.1117/1.JEI.23.5.053025
History: Received June 26, 2014; Revised September 10, 2014; Accepted October 1, 2014
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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.

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© 2014 SPIE and IS&T

Topics

Apertures ; Particles

Citation

Gildardo Lozano-Vega ; Yannick Benezeth ; Franck Marzani and Frank Boochs
"Modular method of detection, localization, and counting of multiple-taxon pollen apertures using bag-of-words", J. Electron. Imaging. 23(5), 053025 (Oct 27, 2014). ; http://dx.doi.org/10.1117/1.JEI.23.5.053025


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