Naval Postgraduate School
Dudley Knox Library
NPS Dudley Knox Library
View Item 
  •   Calhoun Home
  • Theses and Dissertations
  • 1. Thesis and Dissertation Collection, all items
  • View Item
  •   Calhoun Home
  • Theses and Dissertations
  • 1. Thesis and Dissertation Collection, all items
  • View Item
  • How to search in Calhoun
  • My Accounts
  • Ask a Librarian
JavaScript is disabled for your browser. Some features of this site may not work without it.

Browse

All of CalhounCollectionsThis Collection

My Account

LoginRegister

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

Infrared imaging face recognition using nonlinear kernel-based classifiers

Thumbnail
Download
Icon04Dec_Domboulas.pdf (1.687Mb)
Download Record
Download to EndNote/RefMan (RIS)
Download to BibTex
Author
Domboulas, Dimitrios I.
Date
2004-12
Advisor
Fargues, Monique P.
Cristi, Roberto
Karunasiri, Gamani
Metadata
Show full item record
Abstract
In recent years there has been an increased interest in effective individual control and enhanced security measures, and face recognition schemes play an important role in this increasing market. In the past, most face recognition research studies have been conducted with visible imaging data. Only recently have IR imaging face recognition studies been reported for wide use applications, as uncooled IR imaging technology has improved to the point where the resolution of these much cheaper cameras closely approaches that of cooled counterparts. This study is part of an on-going research conducted at the Naval Postgraduate School which investigates the feasibility of applying a low cost uncooled IR camera for face recognition applications. This specific study investigates whether nonlinear kernel-based classifiers may improve overall classification rates over those obtained with linear classification schemes. The study is applied to a 50 subject IR database developed in house with a low resolution uncooled IR camera. Results show best overall mean classification performances around 98.55% which represents a 5% performance improvement over the best linear classifier results obtained previously on the same database. This study also considers several metrics to evaluate the impacts variations in various user-specified parameters have on the resulting classification performances. These results show that a low-cost, low-resolution IR camera combined with an efficient classifier can play an effective role in security related applications.
Rights
Copyright is reserved by the copyright owner.
URI
http://hdl.handle.net/10945/1315
Collections
  • 1. Thesis and Dissertation Collection, all items
NPS Dudley Knox LibraryDUDLEY KNOX LIBRARY
Feedback

411 Dyer Rd. Bldg. 339
Monterey, CA 93943
circdesk@nps.edu
(831) 656-2947
DSN 756-2947

    Federal Depository Library      


Start Your Research

Research Guides
Academic Writing
Ask a Librarian
Copyright at NPS
Graduate Writing Center
How to Cite
Library Liaisons
Research Tools
Thesis Processing Office

Find & Download

Databases List
Articles, Books & More
NPS Theses
NPS Faculty Publications: Calhoun
Journal Titles
Course Reserves

Use the Library

My Accounts
Request Article or Book
Borrow, Renew, Return
Tech Help
Remote Access
Workshops & Tours

For Faculty & Researchers
For International Students
For Alumni

Print, Copy, Scan, Fax
Rooms & Study Spaces
Floor Map
Computers & Software
Adapters, Lockers & More

Collections

NPS Archive: Calhoun
Restricted Resources
Special Collections & Archives
Federal Depository
Homeland Security Digital Library

About

Hours
Library Staff
About Us
Special Exhibits
Policies
Our Affiliates
Visit Us

NPS-Licensed Resources—Terms & Conditions
Copyright Notice

Naval Postgraduate School

Naval Postgraduate School
1 University Circle, Monterey, CA 93943
Driving Directions | Campus Map

This is an official U.S. Navy Website |  Please read our Privacy Policy Notice  |  FOIA |  Section 508 |  No FEAR Act |  Whistleblower Protection |  Copyright and Accessibility |  Contact Webmaster

Export search results

The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

A logged-in user can export up to 15000 items. If you're not logged in, you can export no more than 500 items.

To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.