Share Email Print
cover

Proceedings Paper

Fixed-window image descriptors for image retrieval
Author(s): Leonidas J. Guibas; B. Rogoff; Carlo Tomasi
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We work towards a content-based image retrieval system, where queries can be image-like objects. At entry time, each image is processed to yield a large number of indices into its windows. A window is a square in a fixed quad-tree decomposition of the image, and an index is a fixed-size vector, called a descriptor, similar to the periodograms used in spectral estimation. The fixed decomposition of images was prompted by the need for fast processing, but leads to windows that often straddle image regions with different textural contents, making indices less effective. In this paper, we investigate different definitions of spectral distance which we plan to use to classify windows according to their texture content.

Paper Details

Date Published: 23 March 1995
PDF: 11 pages
Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); doi: 10.1117/12.205305
Show Author Affiliations
Leonidas J. Guibas, Stanford Univ. (United States)
B. Rogoff, Stanford Univ. (United States)
Carlo Tomasi, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 2420:
Storage and Retrieval for Image and Video Databases III
Wayne Niblack; Ramesh C. Jain, Editor(s)

© SPIE. Terms of Use
Back to Top