Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48819
Title: Pollen grains contour analysis on verification approach
Authors: García, Norma Monzón
Chaves, Víctor Alfonso Elizondo
Briceño, Juan Carlos
Travieso, Carlos M. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Object Recognition
Classification
Automation
Texture
Images
Shape
Identification
Microscope
Issue Date: 2012
Journal: Lecture Notes in Computer Science 
Conference: 7th International Conference on Hybrid Artificial Intelligent Systems (HAIS) 
Abstract: Earth's biodiversity has been suffering the effects of human contamination, and as a result there are many species of plants and animals that are dying. Automatic recognition of pollen species by means of computer vision helps to locate specific species and through this identification, study all the diseases and predators which affect this specie, so biologist can improve methods to preserve this species. This work focuses on analysis and classification stages. A classification approach using binarization of pollen grain images, contour and feature extraction to locate the pollen grain objects within the images is being proposed. A Hidden Markov Model classifier was used to classify 17 genders and species from 11 different families of tropical honey bee's plants achieving a mean of 98.77% of success.
URI: http://hdl.handle.net/10553/48819
ISBN: 9783642289415
ISSN: 0302-9743
DOI: 10.1007/978-3-642-28942-2_47
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 7208 LNAI, p. 521-532
Appears in Collections:Actas de congresos
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