6533b833fe1ef96bd129b69e
RESEARCH PRODUCT
Nonlinear radial-harmonic correlation using binary decomposition for scale-invariant pattern recognition
Henri H. ArsenaultPascuala García-martínezsubject
business.industryBinary imageBinary numberPattern recognitionScale invarianceAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsBackground noiseNonlinear systemsymbols.namesakeNoiseOpticsGaussian noiseHarmonicsymbolsArtificial intelligenceElectrical and Electronic EngineeringPhysical and Theoretical ChemistrybusinessMathematicsdescription
We introduce a new scale-invariant pattern-recognition method that uses nonlinear correlation. We applied several common linear correlations to images decomposed into disjoint binary images, which is very discriminant even when the target is embedded in strong noise. We combine our sliced orthogonal nonlinear generalized correlation method and the radial-harmonic expansion in order to achieve scale-invariant pattern recognition. The information from a radial harmonic for each binary slice of the reference object is combined with binary slices of the target. The method avoids the time-consuming process of finding expansion centers for the radial harmonics. The stability of the correlation peaks in the presence of background noise and of overlapping Gaussian noise is also studied.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2003-08-01 | Optics Communications |