System detection and automatic classification of pollen grain applies technical digital imaging process

Authors

  • Jorge Arroyo Hernández Universidad Nacional , Costa Rica Author
  • Carlos M. Travieso González Instituto Universitario para el Desarrollo Tecnológico y la Innovación en Comunicaciones , Costa Rica Author
  • Jaime Ticay Rivas Instituto Universitario para el Desarrollo Tecnológico y la Innovación en Comunicaciones , Costa Rica Author
  • Federico Mora Mora Universidad Nacional , Costa Rica Author
  • Oscar Salas Huertas Universidad Nacional , Costa Rica Author
  • Melvin Ramírez Bogantes Universidad Nacional , Costa Rica Author
  • Luis Sánchez Chavez Universidad Nacional , Costa Rica Author

Keywords:

Pollen, Digital Image Processing, Palynology, Principal Components Analysis (PCA), Neural Networks

Abstract

This paper show the current state of a computer system that will allow the recognition and taxonomic classification of pollen grains of some of the most important tropical honey plants in Costa Rica using techniques of pre and post processing of digital images. The digital system uses filters on the images allowing it to detect and highlights its features and contour. Afterwards it is parametrized and finally a system of neuronal interconnections is used for the automatic recognition of pollen grains. The idea behind the implementation of a computer program is to move from a qualitative to a quantitative paradigm, using different mathematical tools and artificial intelligence in a way that can speed the process of recognition and classification of pollen grains. Using the PCA and the Sum at the outputs (CA) of 30 networks were able to obtain a success rate of 91,67 ± 3,13 which is highly promisisng for the purpose of the automatic classification system.

Downloads

Download data is not yet available.

References

-

Downloads

Published

2013-01-01

Issue

Vol. 27 No. 1 (2013)

Section

Original scientific papers (evaluated by academic peers)

License

Authors who publish with this journal agree to the following terms:

1. Authors guarantee the journal the right to be the first publication of the work as licensed under a Creative Commons License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal https://creativecommons.org/licenses/by-nc-nd/4.0/.

2. Authors can set separate additional agreements for non-exclusive distribution of the version of the work published in the journal (eg, place it in an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.

3. The authors have declared to hold all permissions to use the resources they provided in the paper (images, tables, among others) and assume full responsibility for damages to third parties.

4. The opinions expressed in the paper are the exclusive responsibility of the authors and do not necessarily represent the opinion of the editors or the Universidad Nacional.


Uniciencia Journal and all its productions are under  Creative Commons Atribución-NoComercial-SinDerivadas 4.0 Unported.

There is neither fee for access nor Article Processing Charge (APC)

How to Cite

Arroyo Hernández, J., Travieso González, C. M., Ticay Rivas, J., Mora Mora, F., Salas Huertas, O., Ramírez Bogantes, M., & Chavez, L. S. (2013). System detection and automatic classification of pollen grain applies technical digital imaging process. Uniciencia, 27(1), 59-73. https://www.revistas.una.ac.cr/index.php/uniciencia/article/view/4943