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Proceedings Paper

Eigenspace technique for object characterization in a disaster field
Author(s): Falguni Biswas; M. Ashrafuzzaman; Hideo Nagase
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Paper Abstract

In this paper, we have proposed an application of pattern recognition technique to recognize partially destroyed objects in debris. The study employs an appearance-based eigenspace technique for investigating the representation and recognition of partially destroyed objects, which is one of the severe limitations of this technique. Since the conventional parametric eigenspace technique cannot handle the occluded or even partially destroyed objects, we propose creation of a mean-appearance for representing and recognizing them. The word mean-appearance describes a mean image set, which allows some partially destroyed objects for producing an eigenspace. In the mean image set, averaging of a few destroyed images along with non-destroyed images make a mean appearance, which has less effect of partially destroyed images. In addition, we have proposed to apply eigenspace method to measure lost goods in debris when the conventional method will not be an alternative. The proposed approach is performed using various destroyed objects and experimental results show the effectiveness of the proposed method.

Paper Details

Date Published: 22 May 2003
PDF: 8 pages
Proc. SPIE 5011, Machine Vision Applications in Industrial Inspection XI, (22 May 2003); doi: 10.1117/12.479686
Show Author Affiliations
Falguni Biswas, Kyushu Institute of Technology (Japan)
M. Ashrafuzzaman, Bangladesh Institute of Technology (Bangladesh)
Hideo Nagase, Kyushu Institute of Technology (Japan)

Published in SPIE Proceedings Vol. 5011:
Machine Vision Applications in Industrial Inspection XI
Martin A. Hunt; Jeffery R. Price, Editor(s)

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