Visually Supporting Image Annotation Based on Visual Features and Ontologies

Jalila Filali, Hajer Baazaoui Zghal, Jean Martinet
2017 2017 21st International Conference Information Visualisation (IV)  
Automatic Image Annotation (AIA) is a challenging problem in the field of image retrieval, and several methods have been proposed. However, visually supporting this important tasks and reducing the semantic gap between low-level image features and high-level semantic concepts still remains a key issue. In this paper, we propose a visually supporting image annotation framework based on visual features and ontologies. Our framework relies on three main components: (i) extraction and
more » ... n and classification of features component, (ii) ontology's building component and (iii) image annotation component. Our goal consists on improving the visual image annotation by:(1) extracting invariant and complex visual features; (2) integrating feature classification results and semantic concepts to build ontology and (3) combining both visual and semantic similarities during the image annotation process.
doi:10.1109/iv.2017.27 dblp:conf/iv/FilaliZM17 fatcat:4dw7pfrpmjajpfk5xpx6rb36fi