By Topic

A New Image Thresholding Method Based on Graph Cuts

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)
Wenbing Tao ; Lab. of Service Comput. Technol, Huazhong Univ. of Sci. & Technol., Wuhan, China ; Hai Jin ; Liman Liu

A novel thresholding algorithm is presented to achieve improved image segmentation performance at low computational cost in this paper. The proposed algorithm uses a normalized graph cut measure as the thresholding principle to distinguish an object from the background. The weight matrices used in evaluating the graph cuts are based on the gray levels of an image, rather than the commonly used image pixels. Therefore, the proposed algorithm occupies much smaller storage space and requires much lower computational costs and implementation complexity than other image segmentation algorithms based on graph cuts. This fact makes the proposed algorithm attractive in various real-time vision applications such as automatic target recognition (ATR). A large number of examples are presented to show the superior performance of the proposed thresholding algorithm compared to existing thresholding algorithms.

Published in:

Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on  (Volume:1 )

Date of Conference:

15-20 April 2007