Date of Award

12-1993

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

Steven K. Rogers, PhD

Abstract

In this research, face recognition and speaker identification systems are each converted into verification systems. The two verification systems are then fused to form a single identity verification system. Finally, the use of the Karhunen-Loeve Transform (KLT) for dimensional reduction is examined for suitability in the verification task. The base face recognition system used the KLT for feature reduction and a back-propagation neural net for classification. Verification involved training a net for each individual in the database for two classes of outputs, 'Joe' or 'not Joe.' The base speaker identification system used Cepstral analysis for feature extraction and a distortion measure for classification. Verification in this case involved performing the KLT on the Cepstral coefficients and then classifying using a two-class neural net for each individual, similarly to the face verifier implementation. KLT feature reduction is compared to alternative linear and non-linear methods, and the KLT is found to provide superior performance. The fusion of the two base verification systems is shown to provide superior performance over either system alone.

AFIT Designator

AFIT-GE-ENG-93D-20

DTIC Accession Number

ADA274178

Comments

The author's Vita page is omitted.

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