By Topic

Approach of automatic multithreshold image segmentation based on class variance

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
$33 $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)
Wang Xiaodan ; Dept. of Comput. Eng., Airforce Eng. Univ., ShaanXi, China ; Wu Chongming

In this paper, we extend the automatic one threshold gray-level image segmentation method, propose an approach of automatic multithreshold gray-level image segmentation based on class variance using the classification theory in pattern recognition, and this approach can automatically select the optimum threshold (one or more) of gray-level image. Experimental results show the effectiveness of this method

Published in:

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on  (Volume:4 )

Date of Conference: