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TsoKaDo: An Image Search Engine Performing Recursive Query Recommendation Based on Visual Information

Authors:
Lazaros Tsochatzidis
Athanasios Kapoutsis
Nikos Dourvas
Savvas Chatzichristofis
Yiannis Boutalis
Konstantinos Zagoris

Keywords: Image Retrieval; Metadata; Image Annotation; Query Recommendation Systems.

Abstract:
This paper tackles the problem of the user’s incapability to describe exactly the image that he seeks by introducing an innovative image search engine called TsoKaDo. Until now the traditional web image search was based only on the comparison between metadata of the webpage and the user’s textual description. In the method proposed, images from various search engines are classified based on visual content and new tags are proposed to the user. Recursively, the results get closer to the user’s desire. The aim of this paper is to present a new way of searching, especially in case with less query generality, giving greater weight in visual content rather than in metadata.

Pages: 106 to 111

Copyright: Copyright (c) IARIA, 2012

Publication date: January 30, 2012

Published in: conference

ISSN: 2308-4138

ISBN: 978-1-61208-177-9

Location: Valencia, Spain

Dates: from January 30, 2012 to February 4, 2012