Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/75440
Title: System Detection And Automatic Classification Of Pollen Grain Applies Technical Digital Imaging Process
Authors: Arroyo Hernandez, Jorge 
Travieso Gonzalez, Carlos M. 
Ticay Rivas, Jaime Roberto 
Mora Mora, Federico
Salas Huertas, Oscar
Ramirez Bogantes, Melvin
Sanchez Chaves, Luis
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Pollen
Digital Image Processing
Palynology
Principal Components Analysis (Pca)
Neural Networks
Issue Date: 2013
Journal: Uniciencia 
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.
URI: http://hdl.handle.net/10553/75440
ISSN: 1011-0275
Source: Uniciencia[ISSN 1011-0275],v. 27 (1), p. 59-73, (Enero-Junio 2013)
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