Region and object segmentation algorithms in the QIMERA segmentation platform

  • O'Connor N
  • Sav S
  • Adamek T
  • et al.
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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.

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O’Connor, N., Sav, S., Adamek, T., Mezaris, V., Kompatsiaris, I., Lui, T. Y., … Casas, J. R. (2003). Region and object segmentation algorithms in the QIMERA segmentation platform. In Third International Workshop on Content-Based Multimedia Indexing (CBMI) (p. 1021+8). Rennes: INRIA.

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