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Segmentation stage of a PHMM-based model for off-line recognition of Arabic handwritten city names

机译:基于PHMM的脱线识别模型的分割阶段阿拉伯语手写城市名称

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Offline recognition of handwritten words is a difficult task due to the high variability and uncertainty of human writing. The majority of the recent systems have some constraints such as the limitation of the size of the lexicon to deal with. However, the recognition of city names involves the use of large vocabulary. Therefore, a segmentation stage is necessary to reduce the complexity of the problem. This paper presents the segmentation stage relative to a Planar HMM-based model (PHMM) for off-line recognition of Arabic cursive Tunisian city names, we discuss the different segmentation steps and the variety of problems encountered when performing them. We especially focused on the median zone whose model depend highly on natural and vertical segmentation results.
机译:由于人文写作的高度变化和不确定性,手写单词的离线识别是一项艰巨的任务。最近的大部分系统都有一些限制,例如限制莱克西森的大小来处理。然而,对城市名称的认可涉及使用大型词汇。因此,需要分割阶段来降低问题的复杂性。本文介绍了相对于基于平面的赫姆米的模型(PHMM)的分割阶段,用于阿拉伯法学突尼斯城市名称的离线识别,我们讨论了执行它们时遇到的不同分段步骤和各种问题。我们特别专注于模型依赖于自然和垂直细分结果高度的中位区域。

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