Share Email Print

Proceedings Paper

Content-based object segmentation in video sequences
Author(s): Constantinos Tsougarakis; Sethuraman Panchanathan
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Motivated by the emerging video coding standard MPEG-4, this paper proposes a solution to address the problems of unsupervised object segmentation in images and video sequences, using color information. Although the human visual system is very sensitive to edge information, image segmentation is one of the most fundamental and yet complex tasks in image processing. The correct classification of different elements in a scene into different objects and the accurate extraction of their contours is crucial, since the performance of an object-tracking algorithm relies mainly on the segmentation results. In this paper we propose a novel algorithm for unsupervised object segmentation based on the combination of a region growing algorithm, clustering and a morphological opening by reconstruction operator using the inherent color information present in the image, in order to create a robust segmentation tool.

Paper Details

Date Published: 28 December 1998
PDF: 8 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334634
Show Author Affiliations
Constantinos Tsougarakis, Arizona State Univ. (United States)
Sethuraman Panchanathan, Arizona State Univ. (United States)

Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?