PT Journal
AU Christophe Rigaud
   Clement Guerin
   Dimosthenis Karatzas
   Jean-Christophe Burie
   Jean-Marc Ogier
TI Knowledge-driven understanding of images in comic books
SO International Journal on Document Analysis and Recognition
JI IJDAR
PY 2015
BP 199
EP 221
VL 18
IS 3
DI 10.1007/s10032-015-0243-1
DE Document Understanding; comics analysis; expert system
AB Document analysis is an active field of research, which can attain a complete understanding of the semantics of a given document. One example of the document understanding process is enabling a computer to identify the key elements of a comic book story and arrange them according to a predefined domain knowledge. In this study, we propose a knowledge-driven system that can interact with bottom-up and top-down information to progressively understand the content of a document. We model the comic book’s and the image processing domains knowledge for information consistency analysis. In addition, different image processing methods are improved or developed to extract panels, balloons, tails, texts, comic characters and their semantic relations in an unsupervised way.
ER