Accession Number : ADA114519

Title :   Shift and Scale Invariant Preprocessor.

Descriptive Note : Master's thesis,


Personal Author(s) : Huston,Norman Earl , Jr

PDF Url : ADA114519

Report Date : Dec 1981

Pagination or Media Count : 135

Abstract : A preprocessor is designed to extract a set of features that enhance natural clustering by removing extraneous information. The design removes time shift and scale dependence by taking advantage of invariant properties of a Fourier transform followed by a Mellin transform. The preprocessor is realized using an FFT and a Mellin transform with a conventional error correction term. The error term proves to be indeterminate, but the error's bound is identified as the envelope for Mellin correction terms. Properties of the Mellin transform are employed to modify the signal so that the error correcting is no longer required. The resulting algorithms are tested with variously scaled inputs for which closed form solutions are known. With a verified modification in place, the preprocessor produces features that are invariant to shifting and scaling, while retaining enough information to classify canonic shapes. A method of improving performance is introduced. (Author)

Descriptors :   *Pattern recognition, *Target classification, Radar correlation, Invariance, Preprocessing, Error correction codes, Algorithms, Discrete fourier transforms, Fast fourier transforms, Information transfer, Theses

Subject Categories : Active & Passive Radar Detection & Equipment

Distribution Statement : APPROVED FOR PUBLIC RELEASE