A Knowledge-based Image Retrieval System Integrating Semantic and Visual Features
Olfa Allani, Hajer Baazaoui Zghal, Nédra Mellouli, Herman Akdag · Procedia Computer Science · 2016
The main limitations of the existing high level image retrieval approaches concern the high dependance on an external reliable resource (domain ontologies, learning sets, etc.) and a model for mapping semantic and visual information. In this paper, we propose an image retrieval system integrating semantic and visual features. The idea is to automatically build a modular ontology for semantic information and organize visual features in a graph-based model. Both elements are then combined together in a same component called “pattern” used for retrieval. The system has been implemented and the obtained results show that our proposal enables an improvement in the retrieval task.