Character Segmentation in Asian Collector's Seal Imprints: An Attempt to Retrieval Based on Ancient Character Typeface
Character Segmentation in Asian Collector's Seal Imprints: An Attempt to Retrieval Based on Ancient Character Typeface
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DOI：
10.46298/jdmdh.6102
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发表时间：
2020-02
期刊：
影响因子：
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通讯作者：
Kangying Li;B. Batjargal;Akira Maeda
中科院分区：
文献类型：
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作者：
Kangying Li;B. Batjargal;Akira Maeda
藏家印章为一本书的所有权提供了重要线索。它们包含了许多与古代材料的基本要素有关的信息，还显示了藏书的细节、与书籍的关系、收藏者的身份以及他们的社会地位和财富等。亚洲收藏家通常使用古代艺术人物来制作印章，而不是现代人物。除了主人的名字，还有其他几个词用来表达更深刻的含义。自动识别这些字符的系统可以帮助爱好者和专业人士更好地了解这些海豹的背景信息。然而，由于一些海豹的样本稀少，而且大多数是退化图像，因此缺乏训练数据和标记图像。有必要找到新的方法来充分利用这种稀缺的数据。虽然这些数据可以在网上获得，但它们不包含关于角色位置的信息。这项研究的目的是帮助通过用户交互获得更多的标签数据，并提供仅使用从字体文件中提取的标准字符字体的检索工具。本文提出了一种字符分割方法，无需任何包含字符坐标信息的标注训练数据即可预测候选字符的区域。提出了一种以单个字符为中心的基于检索的印章识别系统，以支持印章的检索和匹配。实验结果表明，本文提出的字符分割方法在亚洲藏家印章上取得了较好的效果，85%的测试数据被正确分割。
Collector's seals provide important clues about the ownership of a book. They contain much information pertaining to the essential elements of ancient materials and also show the details of possession, its relation to the book, the identity of the collectors and their social status and wealth, amongst others. Asian collectors have typically used artistic ancient characters rather than modern ones to make their seals. In addition to the owner's name, several other words are used to express more profound meanings. A system that automatically recognizes these characters can help enthusiasts and professionals better understand the background information of these seals. However, there is a lack of training data and labelled images, as samples of some seals are scarce and most of them are degraded images. It is necessary to find new ways to make full use of such scarce data. While these data are available online, they do not contain information on the characters' position. The goal of this research is to assist in obtaining more labelled data through user interaction and provide retrieval tools that use only standard character typefaces extracted from font files. In this paper, a character segmentation method is proposed to predict the candidate characters' area without any labelled training data that contain character coordinate information. A retrieval-based recognition system that focuses on a single character is also proposed to support seal retrieval and matching. The experimental results demonstrate that the proposed character segmentation method performs well on Asian collector's seals, with 85% of the test data being correctly segmented.