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28 March 1995 Advanced model-based distortion-invariant filters allowing peak variations
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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 NT without an associated drop in the required threshold and thus better object modeling, and better object function energy E minimization (E reduces as NT increase compared to other filters where E increase as NT 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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gregory P. House and David P. Casasent "Advanced model-based distortion-invariant filters allowing peak variations", Proc. SPIE 2490, Optical Pattern Recognition VI, (28 March 1995);


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