Automatic transformation of paper documents into electronic documents requires geometric document layout analysis at the first stage. However, variations in character font sizes, text line spacing, and document layout structures have made it difficult to design a general-purpose document layout analysis algorithm for many years. The use of some parameters has therefore been unavoidable in previous methods. The authors propose a parameter-free method for segmenting the document images into maximal homogeneous regions and identifying them as texts, images, tables, and ruling lines. A pyramidal quadtree structure is constructed for multiscale analysis and a periodicity measure is suggested to find a periodical attribute of text regions for page segmentation. To obtain robust page segmentation results, a confirmation procedure using texture analysis is applied to only ambiguous regions. Based on the proposed periodicity measure, multiscale analysis, and confirmation procedure, we could develop a robust method for geometric document layout analysis independent of character font sizes, text line spacing, and document layout structures. The proposed method was experimented with the document database from the University of Washington and the MediaTeam Document Database. The results of these tests have shown that the proposed method provides more accurate results than previous ones.

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.