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Fuzzy multi-criteria decision making in stereovision matching for fish-eye lenses in forest analysis

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Herrera Caro, Pedro Javier and Pajares Martinsanz, Gonzalo and Guijarro Mata-García, María and Ruz Ortíz, José Jaime and Cruz García, Jesús Manuel de la (2009) Fuzzy multi-criteria decision making in stereovision matching for fish-eye lenses in forest analysis. In Intelligent Data Engineering and Automated Learning, Proceedings. Lecture Notes in Computer Science (5788). Springer-Verlag Berlin, pp. 325-332. ISBN 978-3-642-04393-2

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Official URL: http://link.springer.com/content/pdf/10.1007%2F978-3-642-04394-9_40.pdf


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Abstract

This paper describes a novel stereovision matching approach based on omni-directional images obtained with fish-eye lenses in forest environments. The goal is to obtain a disparity map as a previous step for determining the volume of wood in the imaged area. The interest is focused oil the trunks of the trees. Due to the irregular distribution of the trunks, the most suitable features are the pixels. A set of six attributes is used for establishing the matching between the pixels in both images of each stereo pair analysed. The final decision about the matched pixels is taken based on a well tested FUZZY Multi-Criteria Decision Making approach, where the attributes determine the criteria and the potential matches in one image of the stereo pair for a given pixel in the other one determine the alternatives. The application of this decision making approach makes, the main finding of the paper. The full procedure is based on the application of three well known matching constraints. The proposed approach is compared favourably against the usage of simple features.


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© Springer-Verlag Berlin Heidelberg 2009.
The authors wish to acknowledge to the Council of Education of the Autonomous Community of Madrid and the Social European Fund for the contract with the first author. Also to the Dra. I. Cañellas and F. Montes from the Forest Research Centre for his support and the material supplied. To the DPI2006-15661-C02-01 project.
International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2009) (10th. sep 23-26, 2009. Burgos, España)

Uncontrolled Keywords:Fish-Eye Stereo Vision, Stereovision Matching, Omni-Directional Forest Images, Fuzzy Multi-Criteria Decision Making
Subjects:Sciences > Computer science
ID Code:23094
Deposited On:16 Oct 2013 07:24
Last Modified:05 Mar 2015 10:28

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