Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44044
Title: Pollen classification based on contour features
Authors: Travieso, Carlos M. 
Briceño, Juan C.
Ticay-Rivas, Jaime R.
Alonso, Jesús B. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Hidden Markov models , Support vector machines , Kernel , Shape , Databases , Equations , Mathematical model , Pollen grains , pollen classification , HMM , SVM
Issue Date: 2011
Journal: INES 2011 - 15th International Conference on Intelligent Engineering Systems, Proceedings
Conference: 15th International Conference on Intelligent Engineering Systems, INES 2011 
Abstract: Conserving earth's biodiversity for future generations is a fundamental global task, where automated recognition of pollen species by means of computer vision represents a highly prioritized issue. This work focuses on analysis and classification stages. The morphological details of the contour are proposed as pollen grains discriminative features. The approach has been developed as a robust pollen identification based on an HMM kernel. A Vector Support Machine was used as classifier. The principal contribution in this work, in terms of the use of the HMM is the gradient optimisation problem implementation in the SVM. 47 tropical honey plant species have been classified achieving a mean of 93.8% ± 1.43 of success.
URI: http://hdl.handle.net/10553/44044
ISBN: 9781424489565
DOI: 10.1109/INES.2011.5954712
Source: INES 2011 - 15th International Conference on Intelligent Engineering Systems, Proceedings (5954712), p. 17-21
Appears in Collections:Actas de congresos
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