Principal Component Analysis for Content-based Image Retrieval-Reference-Cited by-同舟云学术

Principal Component Analysis for Content-based Image Retrieval

Published:2002-09 Issue:5 Volume:22 Page:1271-1289
ISSN:0271-5333
Container-title:RadioGraphics
language:en
Short-container-title:RadioGraphics

Author:

Sinha Usha,Kangarloo Hooshang

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiographics.22.5.g02se021271

Reference18 articles.

1. Efficient and effective Querying by Image Content

2. Gupta A, Jain R.Visual information retrieval.Commun Assoc Comput Machinery1997; 40:70-79.

3. Photobook: tools for content-based manipulation of image databases

4. Carson C, Thomas M, Belongie S, Hellerstein JM, Malik J.Blobworld: a system for region-based image indexing and retrieval.Presented at the Third International Conference on Visual Information Systems, Amsterdam, the Netherlands, June 2–4,1999.

5. Ma WY, Manjunath B.Netra: a toolbox for navigating large image databases.Proceedings of the International Conference on Image Processing.Vol 1. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 1997; 568-571.

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