Diversification in an image retrieval system based on text and image processing

Abstract

In this paper we present an image retrieval system created within the research project MUCKE (Multimedia and User Credibility Knowledge Extraction), a CHIST-ERA research project where UAIC{\footnote{"Alexandru Ioan Cuza" University of Iasi}} is one of the partners{\footnote{Together with Technical University from Wienna, Austria, CEA-LIST Institute from Paris, France and BILKENT University from Ankara, Turkey}}. Our discussion in this work will focus mainly on components that are part of our image retrieval system proposed in MUCKE, and we present the work done by the UAIC group. MUCKE incorporates modules for processing multimedia content in different modes and languages (like English, French, German and Romanian) and UAIC is responsible with text processing tasks (for Romanian and English). One of the problems addressed by our work is related to search results diversification. In order to solve this problem, we first process the user queries in both languages and secondly, we create clusters of similar images.

Keywords

• image retrieval
• search diversification
• text processing and image processing