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Book ChapterDOI

Detection of Pollen Grains in Digital Microscopy Images by Means of Modified Histogram Thresholding

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TLDR
The paper describes and investigates the application of the algorithm for the detection and extraction of pollen contour shapes in digital microscopic images based on the Modified Histogram Thresholding, previously employed in the extraction of red blood cells for the automatic diagnosis of certain diseasesbased on the erythrocyte shapes.
Abstract
The paper describes and investigates the application of the algorithm for the detection and extraction of pollen contour shapes in digital microscopic images This is the first step in the process of identification of pollen grains in order to obtain a method for automatic or semi-automatic analysis of air samples The final approach is supposed to support this process by recognizing pollen types in digital microscopic images The applied segmentation approach is based on the Modified Histogram Thresholding, previously employed in the extraction of red blood cells for the automatic diagnosis of certain diseases based on the erythrocyte shapes

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References
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Journal ArticleDOI

Progress towards an automated trainable pollen location and classifier system for use in the palynology laboratory

TL;DR: The potential of the low-cost, automatic, trainable system for the location, recognition and counting of pollen on standard glass microscope slides, designed to dramatically reduce the time that the palynologist must spend at the microscope, is demonstrated, thus considerably increasing productivity in the pollen lab.
Journal ArticleDOI

Pollen texture identification using neural networks

Ping Li, +1 more
- 01 Feb 1999 - 
TL;DR: A new technique, neural network analysis, is briefly introduced, and then applied to the determination of light microscope images of pollen grains, apparently superior to the statistical methods in three ways: high success rates, small number of samples needed for training, and simplicity of features.
Proceedings ArticleDOI

General-purpose object recognition in 3D volume data sets using gray-scale invariants - classification of airborne pollen-grains recorded with a confocal laser scanning microscope

TL;DR: In this paper, a technique is described which may be employed to establish a fully automated system for the recognition of airborne pollens, where 14 invariant gray-scale features based on an integration over the 3D Euclidian transformation group with nonlinear kernels are extracted from these volume data sets.
Journal ArticleDOI

Development of a semi-automatic system for pollen recognition

TL;DR: A semi-automatic system for pollen recognition is studied for the european project ASTHMA to provide accurate pollen concentration measurements and recognition of some pollen types, like Urticaceae or Poaceae or some groups of pollentypes, like reticulate group.
Journal ArticleDOI

Feasibility study on automated recognition of allergenic pollen: grass, birch and mugwort

TL;DR: A feasibility study on the automated recognition of the allergenic relevant pollen, grass, birch, and mugwort, by utilizing digital image analysis and pattern recognition tools found 97.2% were recognized correctly.
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