Histogram of Exclamation Marks and Its Application for Comics Analysis
This paper proposes a histogram formed by counting the number of exclamation marks in comic books for comics analysis. Exclamation marks in comic books are used for expressing character's emotion and are depicted in frequently excited scenes. Also they are easy to detect from different comic books written by various authors. Hence we represent each comic book by its distribution of exclamation marks as a histogram and use such histogram for topic change detection and visualization of relationships between comic books. Experimental results on real comic books show that our bold approach has potential for approximating of contents of comic books by using the proposed histograms.
Robust Frame and Text Extraction from Comic Books
Comic books constitute an important heritage in many countries. Nowadays, digitization allows to search directly from content instead of metadata only (e.g. album title or author name). Few studies have been done in this direction. Only frame and speech balloon extraction have been experimented in the case of simple page structure. In fact, the page structure depends on the author which is why many different structures and drawings exist. Despite the differences, drawings have a common characteristic because of design process: they are all surrounded by a black line. In this paper, we propose to rely on this particularity of comic books to automatically extract frame and text using a connected-component labeling analysis. The approach is compared with some existing methods found in the literature and results are presented.
Ontologies and spatial relations applied to comic books reading.
In this paper, we present a procedure to add semantics to digitized comic books using ontologies. We focus on the panels, computing the reading order thanks to their spatial relations.