Institut für Raumbezogene Informations- und Messtechnik
Hochschule Mainz - University of Applied Sciences

Gildardo Lozano Vega M.Sc.

Gildardo Lozano Vega M.Sc.

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Gildardo Lozano Vega M.Sc.
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We present the sketch of an automatic alternative method for identi-fying and quantifying airborne pollen grains under the framework of a project called Personalized Pollen…

Publikationen

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

2014

Lozano-Vega, G.,
Benezeth, Y.,
Marzani, F.,
Boochs, F.

BibTex

Journal of Electronic Imaging

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.


Analysis of Relevant Features for Pollen Classification

2014

Lozano-Vega, G.,
Benezeth, Y.,
Marzani, F.,
Boochs, F.,
Iliadis, L.,
Maglogiannis, I.,
Papadopoulos, H.

BibTex

Artificial Intelligence Applications and Innovations

Classification of Pollen Apertures Using Bag of Words

2013

Lozano-Vega, G.,
Benezeth, Y.,
Marzani, F.,
Boochs, F.,
Petrosino, A.

BibTex

Image Analysis and Processing – ICIAP 2013

Sketch of an Automatic Image Based Pollen Detection System

2013

Lozano-Vega, G.,
Benezeth, Y.,
Uhler, M.,
Boochs, F.,
Marzani, F.

PDF / BibTex

32. Wissenschaftlich-Technische Jahrestagung der DGPF
We present the sketch of an automatic alternative method for identi-fying and quantifying airborne pollen grains under the framework of a project called Personalized Pollen Profiling and Geospatial Mapping. The first stage of the detection system locates and segments potential pollen particles while re-ducing the dataset size for convenient handling and storing. In the second stage, the proposed classification scheme successively tests different pollen character-istics until the taxon is uniquely identified. Morphological and optical proper-ties of the pollen and image local features are selected based on the study of strengths and weaknesses of the state-of-the-art methods. This scheme allows the system to compute suitable feature vectors to discriminate similar taxa only when necessary, reducing the computational cost.