Synthetic Discriminant Functions For Three-Dimensional Object Recognition

David Casasent; B.V.K. Vijaya Kumar; Vinod Sharma

doi:10.1117/12.934095

23 May 1983 Synthetic Discriminant Functions For Three-Dimensional Object Recognition

David Casasent, B.V.K. Vijaya Kumar, Vinod Sharma

Proceedings Volume 0360, Robotics and Industrial Inspection; (1983) https://doi.org/10.1117/12.934095
Event: 26th Annual Technical Symposium, 1982, San Diego, United States

Abstract

The synthetic discriminant function concept together with its modifications of maximum common information filters and decorrelation transformations are reviewed. We then advance a unified procedure for determining the coefficients for such linear combination filters for recognition of objects in different orientations and from different aspect views. Our formulation utilizes only deterministic techniques and a correlation matrix observation space. This formulation is most attractive for the realization of shift-invariant filters for use in correlator architectures. We then advance the highlights of our initial results on the performance of this new type of generalized shift-invariant filter.

Citation Download Citation

David Casasent, B.V.K. Vijaya Kumar, and Vinod Sharma "Synthetic Discriminant Functions For Three-Dimensional Object Recognition", Proc. SPIE 0360, Robotics and Industrial Inspection, (23 May 1983); https://doi.org/10.1117/12.934095

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