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

A two-stage process for accurate 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 $31
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)

Segmenting images is one of the most important steps in many high-level computer vision algorithms. The ability to divide images up into meaningful regions based upon properties such as shape, texture and colour has still not been fully solved. In this paper we show how good quality segmentations of complex outdoor scenes may be achieved by a two-stage process. The first step is to produce an approximate segmentation using only colour and texture information. The second step is to merge regions by using a neural network trained to classify the regions into one of eleven possible types which correspond to objects types found in outdoor scenes. This stage involves the use of high-level knowledge such as position, shape, context and orientation

Published in:

Image Processing and Its Applications, 1997., Sixth International Conference on  (Volume:2 )

Date of Conference:

14-17 Jul 1997

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.