On parallel lines in noisy forms

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Abstract

Quantification of the rectilinear configuration of typeset rules (lines) opens the way to form classification and content extraction. Line detection on scanned forms is often accomplished with the Hough transform. Here it is followed by simultaneous extraction of the dominant perpendicular sets of extracted lines, which ensures rotation invariance. Translation and scale invariance are attained by using minimal horizontal and vertical sets of distance ratios ("rule gap ratios") instead of rule-edge locations. The ratios are logarithmically mapped to an alphabet so that the resulting symbol strings can be classified by. edit distance. Some probability distributions associated with these steps are derived. Analytical considerations and small-scale experiments on scanned forms suggest that this approach has potential merit for processing degraded forms. © 2014 Springer-Verlag Berlin Heidelberg.

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Nagy, G. (2014). On parallel lines in noisy forms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8621 LNCS, pp. 173–182). Springer Verlag. https://doi.org/10.1007/978-3-662-44415-3_18

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