By Topic

A tensor voting approach for the hierarchical segmentation of 3-D acoustic images

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)
L. Tao ; Dipt. di Informatica, Univ. of Verona, Italy ; V. Murino ; G. Medioni

We present a hierarchical and robust algorithm addressing the problem of filtering and segmentation of three-dimensional acoustic images. This algorithm is based on. the tensor voting approach - a unified computational framework for the inference of multiple salient structures. Unlike most previous approaches, no models or prior information of the underwater environment, nor the intensity information of acoustic images is considered in this algorithm. Salient structures and outlier noisy points are directly clustered in two steps according to both the density and the structural information of input data. Our experimental trials show promising results, very robust despite the low computational complexity.

Published in:

3D Data Processing Visualization and Transmission, 2002. Proceedings. First International Symposium on

Date of Conference: