A Trainable, Single-Pass Algorithm for Column Segmentation

Authors

Son Sylwester, Concordia College, Seward, NEFollow
Sharad C. Seth, University of Nebraska-LincolnFollow

Date of this Version

1995

Comments

Published in Proceedings of the Third International Conference on Document Analysis and Recognition, 1995, Volume 2. doi: 10.1109/ICDAR.1995.601971 Copyright 1995 IEEE. Used by permission.

Abstract

Column Segmentation logically precedes OCR in the document analysis process. The trainable algorithm described here, XYCUT, relies on horizontal and vertical binary profiles to produce an XY- tree representing the column structure of a page of a technical document in a single pass through the bit image. Training against ground truth adjusts a single, resolution independent, parameter using only local information and guided by an edit distance function. The algorithm correctly segments the page image for a (fairly) wide range of parameter values, although small, local and repairable errors may be made, an effect measured by a repair cost function.