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

Inherent Bias and Noise in the Hough Transform

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)
Brown, Christopher M. ; Department of Computer Science, University of Rochester, Rochester, NY 14627.

Considering the Hough transformation as a linear imaging process recasts certain well-known problems, provides a useful vocab-ulary, and possibly indicates a source of applicable literature on the behavior of the Hough transformation in various forms of noise. A consideration of the analytic form of peaks in parameter space sets the stage for the idea of using complementary (negative) votes to cancel off-peak positive votes in parameter space, thus sharpening peaks and reducing bias.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:PAMI-5 ,  Issue: 5 )

Date of Publication:

Sept. 1983

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.