Cart (Loading....) | Create Account
Close category search window
 

Modeling human false target detection decision behavior in infrared images, using a statistical texture image metric

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Aviram, G. ; Dept. of Electr. & Comput. Eng., Ben-Gurion Univ. of the Negev, Beer-Sheva, Israel ; Rotman, S.R.

The ICOM statistical texture image metric incorporates the attributes of global texture matching and of local texture distinctness. The metric is used in this paper to predict human false detection performance (probabilities of false alarms) in both natural and enhanced infrared images, by automatic extraction of the potential false targets in the image. Comparing real experimental data with the metric products reveals very good agreement. Following this result, the metric is used to examine whether the human observer, regarding high and low levels of image clutter, behaves as a constant false alarm rate (CFAR) signal processor, or as a fixed threshold signal processor. It is found that neither one of them is correct. Consequently, a modification to the known CFAR decision behavior model is suggested. The modified model considers the total number of detection decisions (true and false) made by the human observer as the adaptive parameter, instead of the number of only the false detection decisions in the case of the CFAR model. The modified model is tested and confirmed with results obtained both from natural and enhanced images

Published in:

Electrical and ELectronic Engineers in Israel, 2000. The 21st IEEE Convention of the

Date of Conference:

2000

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.