29 August 2016 Uyghur language text detection in images
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Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 1003345 (2016) https://doi.org/10.1117/12.2244133
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China
Text detection in images is an important prerequisite for many image content analysis tasks. Actually, nearly all the widely-used methods focus on English and Chinese text detection while some minority language, such as Uyghur language, text detection is paid less attention by researchers. In this paper, we propose a system which detects Uyghur language text in images. First, component candidates are detected by channel-enhanced Maximally Stable Extremal Regions (MSERs) algorithm. Then, most non-text regions are removed by a two-layer filtering mechanism. Next, the rest component regions are connected into short chains, and the short chains are connected into complete chains. Finally, the non-text chains are pruned by a chain elimination filter. To evaluate our algorithm, we generate a new dataset by various Uyghur texts. As a result, experimental comparisons on the proposed dataset prove that our algorithm is effective for detecting Uyghur Language text in complex background images. The F-measure is 83.5%, much better than the state-of-the- art performance of 75.5%.
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Shun Liu, Hongtao Xie, Jian Yin, and Yajun Chen "Uyghur language text detection in images", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003345 (29 August 2016); doi: 10.1117/12.2244133; https://doi.org/10.1117/12.2244133

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