Title
Knowledge-driven understanding of images in comic books
Abstract
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.
Year
DOI
Venue
2015
10.1007/s10032-015-0243-1
International Journal on Document Analysis and Recognition
Keywords
Field
DocType
Document understanding, Comics analysis, Expert system
Document analysis,Knowledge representation and reasoning,Comics,Information retrieval,Domain knowledge,Computer science,Expert system,Image processing,Semantics,Consistency analysis
Journal
Volume
Issue
ISSN
18
3
1433-2825
Citations 
PageRank 
References 
11
0.61
34
Authors
5
Name
Order
Citations
PageRank
Christophe Rigaud111612.43
Clément Guérin2394.66
Dimosthenis Karatzas340638.13
Jean-Christophe Burie427139.04
Jean-Marc Ogier563185.80