Award Date

5-2009

Degree Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science

First Committee Member

Evangelos A. Yfantis, Chair

Second Committee Member

Jan Pedersen

Third Committee Member

Laxmi P. Gewali

Graduate Faculty Representative

Georg Mauer

Number of Pages

58

Abstract

The objective of this thesis is to discuss the viability of using pyroelectric infrared (PIR) sensors as a biometric system for human identification.

The human body emits infrared radiation, the distribution of which varies throughout the body, and depends upon the shape and composition of the particular body part. A PIR sensor utilizing a Fresnel lens will respond to this infrared radiation. When a human walks, the motion of the body's individual components form a characteristic gait that is likely to affect a PIR sensor field in a unique way.

A statistical model, such as a Hidden Markov Model, could be used for the identification process. The model would consist of two phases; learning and testing. The learning phase would train the model on a particular feature or signature. The testing phase would take a signature as input and determine which of the trained models it matches with the highest probability.

Keywords

Biometric identification; Hidden Markov models; Pattern recognition systems; Signal processing--Digital techniques

Disciplines

Computer Engineering | Signal Processing

Language

English

Comments

Signatures have been redacted for privacy and security measures.


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