We propose a new method independent of parameters for segmenting the document images into maximal homogeneous regions and identifying them as texts, images, tables and lines. A pyramidal quadtree structure is constructed for multiscale analysis and top-down approach, and a periodicity measure is suggested to find a periodical attribute of text regions. To obtain robust page segmentation results, a confirmation procedure using texture analysis is applied to only ambiguous regions. Experimental results with the document database from the University of Washington show that the proposed method works better than the previous ones.
|Number of pages||4|
|Journal||Proceedings - International Conference on Pattern Recognition|
|Publication status||Published - 2000|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition