Embedded object dictionaries for image database browsing and searching
- 23 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 3, 875-878
- https://doi.org/10.1109/icip.1996.560913
Abstract
We describe a technique to encode images for content-based access and retrieval. Potential query terms are first extracted from an image and represented in terms of multiresolution subbands. A vector quantizer structure then maps the subbands of each image object onto a set of embedded dictionaries. An algorithm is used to exploit the occurrence and query probabilities of the objects for efficient coding and retrieval. Furthermore, a new browsing tool based on multiresolution prototypes is proposed. A prototype object is associated with each dictionary entry. Prototype objects may be substituted for subband data for high quality image browsing during retrieval.Keywords
This publication has 6 references indexed in Scilit:
- CODING FOR CONTENT-BASED RETRIEVALPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Query by image and video content: the QBIC systemComputer, 1995
- Picture-queries and picture databasesJournal of Information Science, 1993
- Shape-similarity-based retrieval in image database systemsPublished by SPIE-Intl Soc Optical Eng ,1992
- Vector Quantization and Signal CompressionPublished by Springer Nature ,1992
- An introduction to hidden Markov modelsIEEE ASSP Magazine, 1986