HITHCD-2018: 21k类手写体汉字数据库

Tonghua Su, Wei Pan, Lijuan Yu
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引用次数: 1

摘要

目前的手写体汉字识别(HCCR)是在受限的字符集上进行的,远远不能满足工业需求。本文描述了一个大型手写体汉字数据库的建立。该数据库的建立是为了将中文手写体字符分类任务扩展到GBK字符集规范的完整列表。它包括2.1万个汉字类别和2000万个汉字图像,在规模和多样性上都超过了以往的数据库。我们提出了收集和注释这种大规模手写字符样本的挑战的解决方案。我们精心设计了采样策略,系统地提取了显著信号,并通过三个不同的阶段标注了大量的特征。将该方法推广到其他手写体字符数据库进行了实验,验证了该数据库的应用价值。当然,它的规模为字符识别算法的评估和新技术的开发提供了前所未有的机会。
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HITHCD-2018: Handwritten Chinese Character Database of 21K-Category
Current state of handwritten Chinese character recognition (HCCR) conducted on well-confined character set, far from meeting industrial requirements. The paper describes the creation of a large-scale handwritten Chinese character database. Constructing the database is an effort to scale up Chinese handwritten character classification task to cover the full list of GBK character set specification. It consists of 21-thousand Chinese character categories and 20-million character images, larger than previous databases both in scale and diversity. We present solutions to the challenges of collecting and annotating such large-scale handwritten character samples. We elaborately design the sampling strategy, extract salient signals in a systematic way, annotate the tremendous characters through three distinct stages. Experiments are conducted the generalization to other handwritten character databases and our database demonstrates great values. Surely, its scale opens unprecedented opportunities both in evaluation of character recognition algorithms and in developing new techniques.
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