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

被引：3

作者：

Lozano-Vega, Gildardo ^{[1
,2
]}

Benezeth, Yannick ^{[2
]}

Marzani, Franck ^{[2
]}

Boochs, Frank ^{[1
]}

机构：

[1] Fachhsch Mainz, I3mainz, D-55128 Mainz, Germany

[2] Univ Bourgogne, Le2i, F-21078 Dijon, France

来源：

JOURNAL OF ELECTRONIC IMAGING | 2014年 / 23卷 / 05期

关键词：

object recognition; local binary patterns; bag-of-words; pattern recognition; apertures; palynology; TEXTURE MEASURES; CLASSIFICATION; RECOGNITION; INVARIANTS; IMAGES;

D O I：

10.1117/1.JEI.23.5.053025

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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. (C) 2014 SPIE and IS&T

引用

页数：10

共 23 条

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