Chapter 1: Invited Addresses and Tutorials on Signals, Coding,
  Systems and Intelligent Techniques

Title: Object-driven content-based image retrieval

Author(s): Ioannis Pratikakis, Basilios Gatos, Stavros Perantonis, Iris Vanhamel, Hichem Sahli

Address: Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research |Demokritos|, 153 10 Athens, Greece | Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research |Demokritos|, 153 10 Athens, Greece | Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research |Demokritos|, 153 10 Athens, Greece | Electronics & Informatics Department Vrije Universiteit Brussel, 1050 Brussels,Belgium | Electronics & Informatics Department Vrije Universiteit Brussel, 1050 Brussels,Belgium

Reference: 12th International Workshop on Systems, Signals and Image Processing pp. 189 - 193

Abstract/Summary: This paper presents a novel unsupervised strategy for content-based image retrieval. It is based on a meaningful segmentation procedure that can provide proper distributions for matching via the Earth mover's distance as a similarity metric. The segmentation procedure is based on a hierarchical watershed-driven algorithm that extracts meaningful regions automatically. In this framework, the proposed robust feature extraction and the many-to-many region matching along with the novel region weighting for enhancing feature discrimination play a major role. Experimental results demonstrate the performance of the proposed strategy.

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