Text Detection in Manga by Deep Region Proposal, Classification, and Regression
Wei-Ta Chu, Chih-Chi Yu · 2018
Text in manga presents high variations and different contextual information, and existing scene text detection methods are not directly applicable. We propose two approaches based on deep networks to detect text in manga. In the first approach, features extracted from multiple CNNs are joined and then fed to a combination of a classification network and a regression network. In the second approach, region proposal, feature extraction, and classification/regression, are taken together in a single deep network. The evaluation results show that the first approach achieves performance comparable to the current state of the art, while the second approach yields a big performance leap over existing ones.