Open Access

Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback

  • Vasileios Mezaris1, 2Email author,
  • Ioannis Kompatsiaris2, 3 and
  • Michael G. Strintzis1, 2
EURASIP Journal on Advances in Signal Processing20042004:231946

Received: 31 January 2003

Published: 15 June 2004


An image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segmentation algorithm to divide images into regions and endow the indexing and retrieval system with content-based functionalities. Low-level descriptors for the color, position, size, and shape of each region are subsequently extracted. These arithmetic descriptors are automatically associated with appropriate qualitative intermediate-level descriptors, which form a simple vocabulary termed object ontology. The object ontology is used to allow the qualitative definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword) and their relations in a human-centered fashion. When querying for a specific semantic object (or objects), the intermediate-level descriptor values associated with both the semantic object and all image regions in the collection are initially compared, resulting in the rejection of most image regions as irrelevant. Following that, a relevance feedback mechanism, based on support vector machines and using the low-level descriptors, is invoked to rank the remaining potentially relevant image regions and produce the final query results. Experimental results and comparisons demonstrate, in practice, the effectiveness of our approach.

Keywords and phrases

image retrievalimage databasesimage segmentationontologyrelevance feedbacksupport vector machines

Authors’ Affiliations

Information Processing Laboratory, Electrical and Computer Engineering Department, Aristotle University of Thessaloniki
Centre for Research and Technology Hellas (CERTH), Informatics and Telematics Institute (ITI)
Electrical and Computer Engineering Department, Aristotle University of Thessaloniki


© Mezaris et al. 2004