Classification of Textured and Non-textured Images
Using Region Segmentation
Jia Li, James Z. Wang, Gio Wiederhold
Stanford University, Stanford, CA 94305
The classification of general-purpose photographs into textured and
non-textured images is critical for developing accurate content-based
image retrieval systems for large-scale image databases. With
the accurate detection of textured images, we may retrieve images based on
features tailored for the corresponding image type. In this paper, we
present an algorithm to classify a photographic image as textured or
non-textured using region segmentation and statistical testing. The
application of the system to a database of about $60,000$
general-purpose images shows much improved accuracy in retrieval.
Full Paper in Color
Jia Li, James Z. Wang and Gio Wiederhold, ``Classification of Textured
and Non-Textured Images Using Region Segmentation,'' Proc. IEEE
International Conference on Image Processing (ICIP), Vancouver, BC,
Canada, pp. 754-757, IEEE, September 2000.
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July 10 2000