Forkan, Fadni and Hj Shamsuddin, Siti Mariyam 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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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 (Formerly known)|
|Deposited By:||Liza Porijo|
|Deposited On:||14 Jun 2011 05:15|
|Last Modified:||14 Jun 2011 05:15|
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