Character and Text Recognition of Khmer Historical Palm Leaf Manuscripts
Character and Text Recognition of Khmer Historical Palm Leaf Manuscripts
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高棉历史棕榈叶手稿的字符和文本识别
DOI：
10.1109/icfhr-2018.2018.00012
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
J. Burie
中科院分区：
文献类型：
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作者：
Dona Valy;M. Verleysen;Sophea Chhun;J. Burie
本文介绍了两项针对数字化高棉棕榈叶手稿的历史文献分析任务的方法。第一个任务包括孤立字符识别，使用不同类型的神经网络结构，例如CNN、LSTM-RNN以及两者的组合。第二个任务集中于识别可变长度的单词/文本图像块，并同时定位文本图像中的每个字形。为此，根据高棉文书写系统的特点，分别采用了一维和二维RNN。
This paper presents methods for two historical document analysis tasks on digitized Khmer palm leaf manuscripts. The first task consisting of isolated character recognition is conducted utilizing different types of neural network architectures such as CNN, LSTM-RNN, and a combination of both. The second task focuses on recognizing word/text image patches of variable length and simultaneously localizing each glyph in the text image. For this task, according to the characteristic of Khmer writing system, both one-dimensional and two-dimensional RNN are used.