1998
@inproceedings{RaM1998,
vgclass = {refpap},
vgproject = {cbir},
author = {Srinivas Ravela and R. Manmatha},
title = {On Computing Global Similarity in Images},
booktitle = {Proceedings of the Fourth IEEE Workshop on Applications of Computer Vision (WACV'98)},
address = {Princeton, NJ, USA},
pages = {82--87},
month = {October},
year = {1998},
url = {http://hobart.cs.umass.edu/\~{}mmedia/postscript/mm21.ps.gz},
abstract = {The retrieval of images based on their visual similarity
to an example image is an important and fascinating area of research.
Here, a method to characterize visual appearance for determining global
similarity in images is described.
Images are filtered with Gaussian derivatives and geometric features
are computed from the filtered images. The geometric features used
here are curvature and phase. Two images may be said to be similar if
they have similar distributions of such features. Global similarity
may, therefore, be deduced by comparing histograms of these features.
This allows for rapid retrieval and examples from collection of
gray�level and trademark images are shown.},
}