Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
The state of retrieval system evaluation
Information Processing and Management: an International Journal - Special issue on evaluation issues in information retrieval
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
Statistical structuring of pictorial databases for content-based image retrieval systems
Pattern Recognition Letters
Wavelet-based image indexing techniques with partial sketch retrieval capability
IEEE ADL '97 Proceedings of the IEEE international forum on Research and technology advances in digital libraries
Combining supervised learning with color correlograms for content-based image retrieval
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Image Databases and Multimedia Search
Image Databases and Multimedia Search
Managing Gigabytes: Compressing and Indexing Documents and Images
Managing Gigabytes: Compressing and Indexing Documents and Images
ImageRover: A Content-Based Image Browser for the World Wide Web
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
Texture Features and Learning Similarity
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
A multiscale representation including opponent color features for texture recognition
IEEE Transactions on Image Processing
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
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This paper describes the application of techniques derived from text retrieval research to the content-based querying of image databases. Specifically, the use of inverted files, frequency-based weights and relevance feedback is investigated. The use of inverted files allows very large numbers (≥ O(104)) of possible features to be used, since search is limited to the subspace spanned by the features present in the query image(s). Several weighting schemes used in text retrieval are employed, yielding varying results. We suggest possible modifications for their use with image databases. The use of relevance feedback was shown to improve the query results significantly, as measured by precision and recall, for all users.