Classification of Textured and Non-Textured Images Using Region Segmentation (2000) [9 citations — 4 self]
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by Jia Li, James Ze Wang, Gio Wiederhold
Proc. 7th Int. Conf. on Image Processing
http://www-db.stanford.edu/~wangz/project/imsearch/ICIP2000/wang.pdf
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Abstract:
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. 1.
Citations
| 181 | Simplicity: Semantics-sensitive integrated matching for picture libraries – James, Wang, et al. - 2001 |
| 179 | Wavelets: Algorithms and Applications – Meyer - 1993 |
| 154 | Texture classification and segmentation using wavelet frames – Unser - 1995 |
| 30 | Algorithm AS136: a k-means clustering algorithm – Hartigan, Wong - 1979 |
| 4 | Context based multiscale classification of images – Li, Gray - 1998 |
