Context-based multiscale classification of document images using wavelet coefficient distributions.
In this paper, an algorithm is developed for segmenting document images into four classes: background, photograph, text, and graph. Features used for classification are based on the distribution patterns of wavelet coefficients in high frequency bands. Two important attributes of the algorithm are its multiscale nature-it classifies an image at different resolutions adaptively, enabling accurate classification at class boundaries as well as fast classification overall-and its use of accumulated context information for improving classification accuracy.
Li
J
J
Xerox Palo Alto Research Center, Palo Alto, CA 94304, USA. jiali@isl.stanford.edu
Gray
R M
RM