This article is cited in 1 paper

DATA PROCESSING AND ANALYSIS

Text image normalization using fast Hough transform

P. V. Bezmaternykh<sup>ab

a</sup> Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow
^b Smart Engines Service LLC, Moscow

Abstract: The tasks of text image normalization arise simultaneously in several modules of the automatic document image recognition system. The paper presents a solution for two classical tasks of geometric normalization of a digital text image: compensation for the global document skew angle and slant elimination for its textual fragments. For both tasks, which differ in the type of geometric distortions, the solution is based on a single method of image analysis of the fast Hough transform. This method is specified and two algorithms for solving these problems are proposed, and they are tested: for the task of slant normalization – on a variety of both known dataset and on a specially collected and published dataset of Cyrillic fragments $K_{RUS}$, for the task of document skew normalization – on the popular DISEC dataset. It is shown that a distinctive feature of the proposed method is high speed with the ability to process a large range of angles, and the method itself can be successfully applied in systems for automatic processing of document images.

Keywords: image normalization, fast Hough transform, document image analysis.

DOI: 10.14357/20718632240401

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