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

An Efficient Gray-level Clustering Algorithm for Image Segmentation

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)
Fan-Chei Cheng ; Dept. of Electron. Eng., Huafan Univ., Taipei ; Yu-Kumg Chen ; Kuan-Ting Liu

Gray-level clustering is an important procedure in image processing, which reduces the gray-level of an image. In order to display an image with high gray level in a screen with lower gray level, a good gray-level clustering algorithm is necessary to complete this job. Based on the mean value and standard deviation of histogram within a sub-interval, a novel recursive algorithm for solving the gray-level reduction is proposed in this paper. It divides the sub-interval recursively until the difference between original image and clustered image within a given threshold. Experiments are carried out for some samples with high gray level to demonstrate the computational advantage of the proposed method.

Published in:

Informatics in Control, Automation and Robotics, 2009. CAR '09. International Asia Conference on

Date of Conference:

1-2 Feb. 2009

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.