Share Email Print

Proceedings Paper

Augmented image histogram for image and video similarity search
Author(s): Yu Chen; Edward K. Wong
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

Image histogram is an image feature widely used in content- based image retrieval and video segmentation. It is simple to compute, yet very effective as a feature in detecting image-to-image similarity, or frame-to-frame dissimilarity. While the image histogram captures the global distribution of different intensities or colors well, it does not contain any information about the spatial distribution of pixels. In this paper, we propose to incorporate spatial information into the image histogram, by computing features from the spatial distance between pixels, belonging to the same intensity or color. In addition to the frequency, count of the intensity or color, the mean, variance, and entropy of the distances are computed to form an augmented image histogram. Using the new feature, we performed experiments on a set of color images and a color video sequence. Experimental results demonstrate that the augmented image histogram performs significantly better than the conventional color histogram, both in the image retrieval and video shot segmentation.

Paper Details

Date Published: 17 December 1998
PDF: 10 pages
Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); doi: 10.1117/12.333872
Show Author Affiliations
Yu Chen, Polytechnic Univ. (United States)
Edward K. Wong, Polytechnic Univ. (United States)

Published in SPIE Proceedings Vol. 3656:
Storage and Retrieval for Image and Video Databases VII
Minerva M. Yeung; Boon-Lock Yeo; Charles A. Bouman, Editor(s)

© SPIE. Terms of Use
Back to Top