Similarity-based partial image retrieval guaranteeing same accuracy as exhaustive matching

We propose a new framework for quick and accurate partial image retrieval from a huge number of images based on a predefined distance measure. Finding partial similarities generally requires a huge amount of storage space for indexes due to the large number of portions of images. The proposed method...

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Bibliographic Details
Published in2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763) Vol. 3; pp. 1895 - 1898 Vol.3
Main Authors Kimura, A., Kawanishi, T., Kashino, K.
Format Conference Proceeding
LanguageEnglish
Published Piscataway NJ IEEE 2004
Subjects
Applied sciences
Artificial intelligence
Broadband communication
Computer science; control theory; systems
Discrete cosine transforms
Exact sciences and technology
Image databases
Image retrieval
Image storage
Information retrieval
Information systems. Data bases
Laboratories
Memory organisation. Data processing
Pattern recognition. Digital image processing. Computational geometry
Pixel
Shape
Software
Spatial databases
Multimedia
Database query
Similarity
Image retrieval
Image databank
Information retrieval
Spacing
Case based reasoning
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Summary:We propose a new framework for quick and accurate partial image retrieval from a huge number of images based on a predefined distance measure. Finding partial similarities generally requires a huge amount of storage space for indexes due to the large number of portions of images. The proposed method extracts portions from each database image at a constant spacing, while it extracts all possible portions from a query image. In this way, the proposed method can greatly reduce the size of indexes while theoretically guaranteeing the same accuracy as exhaustive matching.
ISBN:9780780386037
0780386035
DOI:10.1109/ICME.2004.1394629