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

Gildardo Lozano-Vega; Yannick Benezeth; Franck Marzani; Frank Boochs

doi:10.1117/1.JEI.23.5.053025

27 October 2014 Modular method of detection, localization, and counting of multiple-taxon pollen apertures using bag-of-words

Gildardo Lozano-Vega, Yannick Benezeth, Franck Marzani, Frank Boochs

Author Affiliations +

Journal of Electronic Imaging, Vol. 23, Issue 5, 053025 (October 2014). https://doi.org/10.1117/1.JEI.23.5.053025

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.

Citation Download 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," Journal of Electronic Imaging 23(5), 053025 (27 October 2014). https://doi.org/10.1117/1.JEI.23.5.053025

Published: 27 October 2014

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