Improved Thai text detection from natural scenes

K. Woraratpanya, Pimlak Boonchukusol, Y. Kuroki, Yasushi Kato
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引用次数: 10

Abstract

Thai text detection from natural scenes is still a challenging task for language translation applications, since there are many unsolved issues. Furthermore, the existing related works cannot completely detect Thai text. The main reason is that Thai text layout has vowels and tonal marks that differ from other languages. This paper proposes an approach to detect Thai text from natural scenes. The approach consists of two main procedures. (i) Fast boundary clustering algorithm decomposes scene features into multilayers, so that it is faster and easier to analyze Thai text characters. (ii) Modified connected component analysis method is applied to such scene features in order to detect Thai text boundaries. Based on 150 test images with 4,920 characters, the experimental results demonstrate that the proposed approach achieves the high average precision and recall, 0.80 and 0.90.
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改进了自然场景的泰语文本检测
对于语言翻译应用来说,从自然场景中检测泰语文本仍然是一项具有挑战性的任务,因为有许多尚未解决的问题。此外,现有的相关工作不能完全检测泰文。主要原因是泰语文本布局的元音和音调标记与其他语言不同。本文提出了一种从自然场景中检测泰语文本的方法。该方法包括两个主要步骤。(i)快速边界聚类算法将场景特征分解成多层,从而更快更容易地分析泰文文本字符。(ii)将改进的连通分量分析方法应用于这些场景特征,以检测泰文文本边界。基于150幅4,920个字符的测试图像,实验结果表明,该方法达到了较高的平均准确率和召回率,分别为0.80和0.90。
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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