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Kohonen-swarm algorithm for unstructured data in surface reconstruction

Forkan, Fadni and Hj Shamsuddin, Siti Mariyam (2008) Kohonen-swarm algorithm for unstructured data in surface reconstruction. In: Proceedings - Computer Graphics, Imaging and Visualisation, Modern Techniques and Applications, CGIV. Institute of Electrical and Electronics Engineers, New York, pp. 5-11. ISBN 978-076953359-9

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Abstract

This work introduces a new method for surface reconstruction based on hybrid soft computing techniques: Kohonen Network and Particle Swarm Optimization (PSO). Kohonen network learns the sample data through mapping grid that can grow. The implementation is executed by generating Kohonen mapping framework of the data subsequent to the learning process. Consequently, the learned and well-represented data become the input for surface fitting procedure, and in this study, PSO is proposed to probe the optimum fitting points on the surfaces. The proposed algorithms are applied on different types of curve and surfaces to observe its ability in reconstructing the objects while preserving the original shapes. The experimental results have shown that the proposed algorithm have succeeded in producing the reconstructed surfaces with minimum errors generated.

Item Type:Book Section
Additional Information:ISBN:978-076953359-9; 5th International Conference on Computer Graphics, Imaging and Visualisation, Modern Techniques and Applications, CGIV; Penang; 26 August 2008 through 28 August 2008
Uncontrolled Keywords:growing grid, kohonen network, particle swarm optimization, surface reconstruction
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:12610
Deposited By: Liza Porijo
Deposited On:14 Jun 2011 05:15
Last Modified:07 Sep 2017 04:09

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