Applying Computer Vision Systems to Historical Book Illustrations: Challenges and First Results (original) (raw)

Digital humanities still need to unlock the potential of images anlysis algorithms to a large extent. Modern deep learning images processing can contribute much to quantify knowledge about visual components in books. In this study, we report on experiments carried out for historical print. The illustrations in books offer much for humanities research. Object recognition systems can identify the portfolio of objects in book illustrations. In a study with several hundreds of books, we applied systems to find illustrations and classify them. Results show that persons are shown in illustrations within fiction books with a higher frequency than in non-fiction books. We also show the classification results for an analysis of the printing technology. This expert task can still not be perfectly modeled by a CNN. A class activation map analysis can be used to analyze the performance qualitatively.