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Proceedings Paper

Constraining deformable templates for shape recognition
Author(s): Teresa Aixut; Yuri L. de Meneses; Fabien Bourgeois; Jacques Jacot
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Paper Abstract

This paper addresses the problem of robust shape recognition in the presence of shape deformation as well as changes in part position, orientation and scale. Point Distribution Model (PDM) are deformable templates that have interesting features for industrial inspection tasks, since they are built by statistical analysis of a training set and they define a prototype shape as well a set of possible, acceptable deformations. To further improve their classification capabilities, these deformable templates are extended by adding a constraint on the amount of deformation. A constrained optimization procedure is proposed and successfully tested on an industrial inspection task.

Paper Details

Date Published: 1 May 2003
PDF: 10 pages
Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); doi: 10.1117/12.514930
Show Author Affiliations
Teresa Aixut, Swiss Federal Institute of Technology Lausanne (Switzerland)
Yuri L. de Meneses, Swiss Federal Institute of Technology Lausanne (Switzerland)
Fabien Bourgeois, Swiss Federal Institute of Technology Lausanne (Switzerland)
Jacques Jacot, Swiss Federal Institute of Technology Lausanne (Switzerland)


Published in SPIE Proceedings Vol. 5132:
Sixth International Conference on Quality Control by Artificial Vision
Kenneth W. Tobin; Fabrice Meriaudeau, Editor(s)

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