Multi-scale techniques for document page segmentation

Page segmentation algorithms found in published literatures often rely on some predetermined parameters such as general font sizes, distances between text lines and document scan resolutions. Variations of these parameters in real document images greatly affect the performance of the algorithms. In this paper, we present a novel approach for document page segmentation using a multi-scale technique. An efficient implementation of a local connectivity algorithm transforms a document image into a parameter domain in which a parameter value at a pixel location represents a connectivity property for its neighboring foreground pixels in the original document image. Then a top-down approach with a linear search reveals the document regions at each scale levels as text block, text lines and graphics. We consider our algorithm a transform based multi-scale method. Our ongoing research shows that the algorithm is robust for variations of document parameters.