By Topic

Range Image Feature Extraction with Varying Degrees of Data Irregularity

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

3 Author(s)

The use of range images has become prominent in the field of computer vision. Due to the irregular nature of range image data that occurs with a number of sensors, edge detection techniques for range images are often based on scan line data approximations and hence do not employ exact data locations. We present a finite element based approach to the development of gradient operators that can be applied to both regularly and irregularly distributed range images. We have created synthetic irregularly distributed range images for each edge type, and the gradient operators developed are evaluated with respect to their performance in edge detection across varying levels of data irregularity.

Published in:

Machine Vision and Image Processing Conference, 2007. IMVIP 2007. International

Date of Conference:

5-7 Sept. 2007