Pattern recognition invariant under changes of scale and orientation

Henri H. Arsenault; Sebastien Parent; Sylvain Moisan

doi:10.1117/12.281296

19 August 1997 Pattern recognition invariant under changes of scale and orientation

Henri H. Arsenault, Sebastien Parent, Sylvain Moisan

Proceedings Volume 3101, New Image Processing Techniques and Applications: Algorithms, Methods, and Components II; (1997) https://doi.org/10.1117/12.281296
Event: Lasers and Optics in Manufacturing III, 1997, Munich, Germany

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.

Citation Download Citation

Henri H. Arsenault, Sebastien Parent, and Sylvain Moisan "Pattern recognition invariant under changes of scale and orientation", Proc. SPIE 3101, New Image Processing Techniques and Applications: Algorithms, Methods, and Components II, (19 August 1997); https://doi.org/10.1117/12.281296

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