VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Efficient use of local edge histogram descriptor
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Ontology-Based Photo Annotation
IEEE Intelligent Systems
Blobworld: A System for Region-Based Image Indexing and Retrieval
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization
Curvature Scale Space Representation: Theory, Applications, and MPEG-7 Standardization
An Ontology-based Approach to Retrieve Digitized Art Images
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Region-based image retrieval using an object ontology and relevance feedback
EURASIP Journal on Applied Signal Processing
Statistical modeling and conceptualization of natural images
Pattern Recognition
Fusing MPEG-7 visual descriptors for image classification
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
An intelligent user interface for browsing and searching MPEG-7 images using concept lattices
CLA'06 Proceedings of the 4th international conference on Concept lattices and their applications
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One of the big issues facing current content-based image retrieval is how to automatically extract the semantic information from images In this paper, we propose an efficient method that automatically extracts the semantic information from images by using ontologies and the semantic inference rules In our method, MPEG-7 visual descriptors are used to extract the visual features of image which are mapped to the semi-concept values We also introduce the visual and animal ontology which are built to bridge the semantic gap The visual ontology facilitates the mapping between visual features and semi-concept values, and allows the definition of relationships between the classes describing the visual features The animal ontology representing the animal taxonomy can be exploited to identify the object in an image We also propose the semantic inference rules that can be used to automatically extract high-level concepts from images by applying them to the visual and animal ontology Finally, we discuss the limitations of the proposed method and the future work.