Annotation-Free Character Detection in Historical Vietnamese Stele Images
| Autor: | Anna Scius-Bertrand, Beat Wolf, Marc Bui, Andreas Fischer, Michael Jungo |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Character (computing)
business.industry Computer science Vietnamese Document analysis computer.software_genre language.human_language Object detection Annotation Keyword spotting ComputingMethodologies_DOCUMENTANDTEXTPROCESSING language Artificial intelligence Transcription (software) business computer Natural language processing |
| Zdroj: | Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030865481 ICDAR (1) |
| DOI: | 10.1007/978-3-030-86549-8_28 |
| Popis: | Images of Historical Vietnamese stone engravings provide historians with a unique opportunity to study the past of the country. However, due to the large heterogeneity of thousands of images regarding both the text foreground and the stone background, it is difficult to use automatic document analysis methods for supporting manual examination, especially with a view to the labeling effort needed for training machine learning systems. In this paper, we present a method for finding the location of Chu Nom characters in the main text of the steles without the need of any human annotation. Using self-calibration, fully convolutional object detection methods trained on printed characters are successfully adapted to the handwritten image collection. The achieved detection results are promising for subsequent document analysis tasks, such as keyword spotting or transcription. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|