Browse DORAS
Browse Theses
Search
Latest Additions
Creative Commons License
Except where otherwise noted, content on this site is licensed for use under a:

Region and object segmentation algorithms in the Qimera segmentation platform

O'Connor, Noel E. and Sav, Sorin and Adamek, Tomasz and Mezaris, Vasileios and Kompatsiaris, Ioannis and Lui, Tsz Ying and Izquierdo, Ebroul and Bennström, Christian Ferran and Casas, Josep R. (2003) Region and object segmentation algorithms in the Qimera segmentation platform. In: CBMI 2003 - International Workshop on Content-Based Multimedia Indexing, 22-24 September 2003, Rennes, France.

Full text available as:

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
411Kb

Abstract

In this paper we present the Qimera segmentation platform and describe the different approaches to segmentation that have been implemented in the system to date. Analysis techniques have been implemented for both region-based and object-based segmentation. The region-based segmentation algorithms include: a colour segmentation algorithm based on a modified Recursive Shortest Spanning Tree (RSST) approach, an implementation of a colour image segmentation algorithm based on the K-Means-with-Connectivity-Constraint (KMCC) algorithm and an approach based on the Expectation Maximization (EM) algorithm applied in a 6D colour/texture space. A semi-automatic approach to object segmentation that uses the modified RSST approach is outlined. An automatic object segmentation approach via snake propagation within a level-set framework is also described. Illustrative segmentation results are presented in all cases. Plans for future research within the Qimera project are also discussed.

Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Subjects:Computer Science > Image processing
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Official URL:http://www.irisa.fr/manifestations/2003/CBMI03/indexGB.htm
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:EU IST-2000-32795, Enterprise Ireland
ID Code:389
Deposited On:01 Apr 2008 by DORAS Administrator. Last Modified 07 May 2010 10:58

Download statistics

Archive Staff Only: edit this record