@inproceedings{Ji:2003:NCB,
optnote = {},
author = {Xiaowen Ji and Zoltan Kato and Zhiyong Huang},
optkey = {},
optannote = {},
optseries = {},
editor = {Jon Rokne and Reinhard Klein and Wenping Wang},
localfile = {papers/Ji.2003.NCB.pdf},
address = {Los Alamitos, CA},
publisher = {IEEE},
organization = {IEEE Computer Society},
doi = {http://dx.doi.org/10.1109/PCCGA.2003.1238257},
optmonth = {},
optcrossref = {},
booktitle = {Proceedings of Pacific Graphics 2003},
optvolume = {},
title = {{N}on-{P}hotorealistic {R}endering and {C}ontent-{B}ased {I}mage
{R}etrieval},
optnumber = {},
abstract = {In this paper, we will show how non-photorealistic rendering (NPR)
can take a new role in content-based image retrieval (CBIR). The
proposed CBIR method applies a novel image similarity measure:
Unlike traditional features like color, texture, or shape, our
measure is based on a painted representation of the original
image. This is produced by a stochastic paintbrush algorithm which
simulates a painting process. We use the stroke parameters (color,
size, orientation, and location) as features and similarity is
measured by matching strokes of a pair of images. The advantage of
our approach is that it provides information not only about the
color content but also about the structural properties of an image
without the segmentation of the image. Experimental results show
that the CBIR method using paintbrush features has higher
retrieval rate than traditional methods using color or texture
features only.},
year = {2003},
pages = {153--160},
}
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