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Proceedings Paper

Pattern recognition invariant under changes of scale and orientation
Author(s): Henri H. Arsenault; Sebastien Parent; Sylvain Moisan
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Paper Abstract

We have used a modified method proposed by neiberg and Casasent to successfully classify five kinds of military vehicles. The method uses a wedge filter to achieve scale invariance, and lines in a multi-dimensional feature space correspond to each target with out-of-plane orientations over 360 degrees around a vertical axis. The images were not binarized, but were filtered in a preprocessing step to reduce aliasing. The feature vectors were normalized and orthogonalized by means of a neural network. Out-of-plane rotations of 360 degrees and scale changes of a factor of four were considered. Error-free classification was achieved.

Paper Details

Date Published: 19 August 1997
PDF: 7 pages
Proc. SPIE 3101, New Image Processing Techniques and Applications: Algorithms, Methods, and Components II, (19 August 1997); doi: 10.1117/12.281296
Show Author Affiliations
Henri H. Arsenault, COPL/Univ. Laval (Canada)
Sebastien Parent, COPL/Univ. Laval (Canada)
Sylvain Moisan, COPL/Univ. Laval (Canada)


Published in SPIE Proceedings Vol. 3101:
New Image Processing Techniques and Applications: Algorithms, Methods, and Components II
Philippe Refregier; Rolf-Juergen Ahlers, Editor(s)

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