Refereed full papers (journals, book chapters, international conferences)

1994

@inproceedings{SmC1994a,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{John R. Smith and Shih-Fu Chang},
	title =	{Quad-Tree Segmentation for Texture-Based Image Query},
	booktitle =	{Proceedings of The Second ACM International Multimedia Conference ({ACM} {M}ultimedia 94)},
	address =	{San Francisco, CA, USA},
	pages =	{279--286},
	publisher =	{ACM Press},
	month =	{October~15--10},
	year =	{1994},
	url =	{ftp://ftp.ee.columbia.edu/pub/CTR-Research/advent/public/papers/94/smith94a.pdf},
	url1 =	{ftp://ftp.ee.columbia.edu/pub/CTR-Research/advent/public/papers/94/smith94a.ps.gz},
	abstract =	{In this paper we propose a technique for segmenting images by
	texture content with application to indexing images in a large image
	database. Using a quad-tree decomposition, texture features are extracted
	from spatial blocks at a hierarchy of scales in each image. The quad-tree
	is grown by iteratively testing conditions for splitting parent blocks
	based on texture content of children blocks. While this approach does not
	achieve smooth identification of texture region borders, homogeneous blocks
	of texture are extracted which can be used in a database index.
	Furthermore, this technique performs the segmentation directly using image
	spatial-frequency data. In the segmentation reported here, texture features
	are extracted from the wavelet representation of the image. This method
	however, can use other subband decompositions including Discrete Cosine
	Transform (DCT), which has been adopted by the JPEG standard for image
	coding. This makes our segmentation method extremely applicable to
	databases containing compressed image data. We show application of the
	texture segmentation towards providing a new method for searching for
	images in large image databases using ``Query-by-texture.''},
}