Authors:
Hanen Karamti
;
Mohamed Tmar
and
Faiez Gargouri
Affiliation:
Université de Sfax, Tunisia
Keyword(s):
Content Based Image Retrieval, Image, Retrieval Model, Neural Network, Query, Vector Space Model.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Information Systems Analysis and Specification
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Methodologies and Methods
;
Multimedia Systems
;
Neural Network Software and Applications
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Semiotics
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Symbolic Systems
;
Theory and Methods
Abstract:
The rapid development of digitization and data storage techniques resulted in images’ volume increase. In order to cope with this increasing amount of informations, it is necessary to develop tools to accelerate and facilitate the access to information and to ensure the relevance of information available to users. These tools must minimize the problems related to the image indexing used to represent content query information. The present paper is at the heart of this issue. Indeed, we put forward the creation of a new retrieval model based on a neural network which transforms any image retrieval process into a vector space model. The results obtained by this model are illustrated through some experiments.