Gabor Filter Polynomial Approximation Based On A Novel Evolutionary Stochastic Technique

Keywords

Approximation algorithms; Approximation methods; Gabor filters; Hardware; Root mean square; Signal processing algorithms; Stochastic processes

Abstract

A new particle swarm optimization (PSO) algorithm has been developed, and combined with the differential evolution (DE) method. The novel evolutionary technique is utilized to approximate the sine and Gaussian functions of a Gabor filter, as polynomial functions, by the stochastic computation of an optimal set of coefficients. The new stochastic algorithm achieves a lower root mean square error of 0.0185, in comparison to sine and Gaussian approximations using state-machines from another work. Another important feature that adds more value to this work is the fact that polynomial functions can be constructed in hardware, through relatively simply operations, such as shift-add operations.

Publication Date

12-14-2015

Publication Title

Proceedings - IEEE Military Communications Conference MILCOM

Volume

2015-December

Number of Pages

1138-1143

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/MILCOM.2015.7357599

Socpus ID

84959260962 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84959260962

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