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

On the relation of order-statistics filters and template matching: optimal morphological pattern recognition

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

1 Author(s)
Schonfeld, D. ; Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA

In this paper, we investigate methods for optimal morphological pattern recognition. The task of optimal pattern recognition is posed as a solution to a hypothesis testing problem. A minimum probability of error decision rule-maximum a posteriori filter-is sought. The classical solution to the minimum probability of error hypothesis testing problem, in the presence of independent and identically distributed noise degradation, is provided by template matching (TM). A modification of this task, seeking a solution to the minimum probability of error hypothesis testing problem, in the presence of composite (mixed) independent and identically distributed noise degradation, is demonstrated to be given by weighted composite template matching (WCTM). As a consequence of our investigation, the relationship of the order-statistics filter (OSF) and TM-in both the standard as well as the weighted and composite implementations-is established. This relationship is based on the thresholded cross-correlation representation of the OSF. The optimal order and weights of the OSF for pattern recognition are subsequently derived. An additional outcome of this representation is a fast method for the implementation of the OSF

Published in:

Image Processing, IEEE Transactions on  (Volume:9 ,  Issue: 5 )

Date of Publication:

May 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.