Metaheuristic approach to optical character recognition of Old Slavic letters

S. Panov, S. Koceski
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Abstract

This paper introduces a metaheuristic approach to the problem of OCR of Old Slavic letters. This approach consists of several sequential stages: filtering, binarization, skeletonization, feature extraction and decision tree classification. The image preprocessing steps proved to provide improvements to the correctness of the letter classification, since the quality of the filtered image influences the feature extraction phase, which is based on the unique characteristics of the Old Slavic letters. Various verifications of this approach were performed and the correctness of this approach has been proven.
古斯拉夫字母光学字符识别的元启发式方法
本文介绍了一种元启发式方法来解决古斯拉夫字母的OCR问题。该方法由几个连续的阶段组成:滤波、二值化、骨架化、特征提取和决策树分类。事实证明,图像预处理步骤提高了字母分类的正确性,因为过滤图像的质量会影响基于古斯拉夫字母独特特征的特征提取阶段。对该方法进行了各种验证,并证明了该方法的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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