@string{pg="Proceedings of Pacific Conference on Computer Graphics and Applications"}
@InProceedings{Ji-etal2003,
  author =	 {Ji, Xiaowen and Kato, Zoltan and Huang, Zhiyong},
  title =	 {Non-Photorealistic Rendering and Content-Based Image
                  Retrieval},
  booktitle =	 pg,
  pages =	 {153--162},
  year =	 2003,
  address =	 {Canmore, Canada},
  month =	 oct,
  organization = {IEEE},
  pdf =		 {papers/pg2003.pdf},
  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.}
}