Share Email Print
cover

Proceedings Paper

Synthetic Discriminant Functions For Three-Dimensional Object Recognition
Author(s): David Casasent; B.V.K. Vijaya Kumar; Vinod Sharma
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 23 May 1983
PDF: 7 pages
Proc. SPIE 0360, Robotics and Industrial Inspection, (23 May 1983); doi: 10.1117/12.934095
Show Author Affiliations
David Casasent, Carnegie-Mellon University (United States)
B.V.K. Vijaya Kumar, Carnegie-Mellon University (United States)
Vinod Sharma, Carnegie-Mellon University (United States)


Published in SPIE Proceedings Vol. 0360:
Robotics and Industrial Inspection
David P. Casasent, Editor(s)

© SPIE. Terms of Use
Back to Top