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Proceedings Paper

Inverted image indexing and compression
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Paper Abstract

Inverted file indexing and its compression have proved to be highly successful for free-text retrieval. Although the 'inverted' nature of the data structure provides an efficient mechanism for searching key words or terms in large documents, for image retrieval, the application of inverted files to the title, caption, or description of the images are not sufficient. One must be able to index and retrieve images based on the visual contents. Many content-based image retrieval techniques are used for the images as a whole picture. Analogous to free-text retrieval, a novel technique, called inverted image indexing and compression, is proposed in this paper. Similar to works in a document, each image can have multiple areas which are perceived to be meaningful visual contents. These areas are selected by users and then undergo two processes: automatic signature generation based on wavelet signatures, and users specification of high-level contents using ternary fact model. The contents in compressed form are inserted into an inverted image file. The concept of composite bitplane signature is also introduced.

Paper Details

Date Published: 6 October 1997
PDF: 10 pages
Proc. SPIE 3229, Multimedia Storage and Archiving Systems II, (6 October 1997); doi: 10.1117/12.290346
Show Author Affiliations
Simon Wing-Wah So, Victoria Univ. of Technology (Australia)
Clement H. C. Leung, Victoria Univ. of Technology (Australia)


Published in SPIE Proceedings Vol. 3229:
Multimedia Storage and Archiving Systems II
C.-C. Jay Kuo; Shih-Fu Chang; Venkat N. Gudivada, Editor(s)

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