Text detection in manga by combining connected-component-based and region-based classifications
Yuji Aramaki, Yusuke Matsui, Toshihiko Yamasaki, Kiyoharu Aizawa · 2016
As manga (Japanese comics) have become common content in many countries, it is necessary to search manga by text query or translate them automatically. For these applications, we must first extract texts from manga. In this paper, we develop a method to detect text regions in manga. Taking motivation from methods used in scene text detection, we propose an approach using classifiers for both connected components and regions. We have also developed a text region dataset of manga, which enables learning and detailed evaluations of methods used to detect text regions. Experiments using the dataset showed that our text detection method performs more effectively than existing methods.