By Topic

Automated threshold detection using a pyramid data structure

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

3 Author(s)
Jiang, T. ; Biomed. Eng., Virginia Univ., Charlottesville, VA, USA ; Merickel, M.B. ; Parrish, E.A.

An approach to detect the thresholds automatically in a noisy histogram is discussed. The histogram is considered as a 1D image. Then, a histogram pyramid is built for smoothing the noisy histogram and eliminating the small noise peaks and valleys. The threshold is first found at the higher level of the histogram pyramid and then mapped back to the successive levels. The results show that the thresholds obtained are close to the optimal solution in terms of the statistical point of view and are of reasonable values in some complicated and noisy histograms

Published in:

Pattern Recognition, 1988., 9th International Conference on

Date of Conference:

14-17 Nov 1988