6533b851fe1ef96bd12aa0bc

RESEARCH PRODUCT

Invariant pattern recognition based on 1-D Wavelet functions and the polynomial decomposition

David MendlovicCarlos FerreiraZeev ZalevskyIdo RavehGal ShabtayJavier Garcia

subject

Polynomial decompositionbusiness.industryAtomic and Molecular Physics and OpticsInvariant pattern recognitionInvariant extended Kalman filterElectronic Optical and Magnetic MaterialsOpticsWaveletReal-valued functionElectrical and Electronic EngineeringPhysical and Theoretical ChemistryInvariant (mathematics)businessAlgorithmPolynomial expansionScalingMathematics

description

Abstract A new filter, consisting of 1-D Wavelet functions is suggested for achieving optical invariant pattern recognition. The formed filter is actually a real function, hence, it is theoretically possible to be implemented under both spatially coherent and spatially incoherent illuminations. The filter is based on the polynomial expansion, and is constructed out of a scaled bank of filters multiplied by 1-D Wavelet weight functions. The obtained output is shown to be invariant to 2-D scaling even when different scaling factors are applied on the different axes. The computer simulations and the experimental results demonstrate the potential hidden in this technique.

yearjournalcountryeditionlanguage
1997-03-01Optics Communications
https://doi.org/10.1016/s0030-4018(96)00701-8