We consider a new detection application for distortion-invariant filters. Several new advances to the MINACE filter are considered. These include: improved object modeling (this provides scene correlation plane peaks near the specified values), improved clutter modeling (no false class training is used), a new trade-off parameter c definition (with the energy of each spectra normalized to one), use of a smaller filter size and a prime factor FFT (this reduces noise effects), zero-mean filters (these allow detection of hot and cold contrast objects), etc. We advance a new peak variance degree of freedom distortion-invariance filter (PVDDF) with many attractive new properties. These advantages include: insurance that the correlation peak values for all distorted objects are close to a given value without requiring that each object have a given correlation peak value (in practice one does not want all distorted object inputs to give the same exact correlation peak value), use of more training images N_T without an associated drop in the required threshold and thus better object modeling, and better object function energy E minimization (E reduces as N_T increase compared to other filters where E increase as N_T increases). This new filter thus achieves both better correlation peak values and better energy minimization (prior filters cannot achieve both goals) by using degrees of freedom.

Date Published: 28 March 1995
PDF: 11 pages
Proc. SPIE 2490, Optical Pattern Recognition VI, (28 March 1995); doi: 10.1117/12.205806

Published in SPIE Proceedings Vol. 2490:
Optical Pattern Recognition VI
David P. Casasent; Tien-Hsin Chao, Editor(s)