Sketch-based manga retrieval using manga109 dataset

Manga (Japanese comics) are popular worldwide. However, current e-manga archives offer very limited search support, i.e., keyword-based search by title or author. To make the manga search experience more intuitive, efficient, and enjoyable, we propose a manga-specific image retrieval system. The pro...

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Bibliographic Details
Published in:	Multimedia tools and applications 2017-10, Vol.76 (20), p.21811-21838
Main Authors:	Matsui, Yusuke, Ito, Kota, Aramaki, Yuji, Fujimoto, Azuma, Ogawa, Toru, Yamasaki, Toshihiko, Aizawa, Kiyoharu
Format:	Article
Language:	eng
Subjects:	Artists Comics Computer Communication Networks Computer Science Data Structures and Information Theory Datasets Image management Image retrieval Interactive systems Manga Multimedia Information Systems Searching Special Purpose and Application-Based Systems
Online Access:	Get full text
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Summary:	Manga (Japanese comics) are popular worldwide. However, current e-manga archives offer very limited search support, i.e., keyword-based search by title or author. To make the manga search experience more intuitive, efficient, and enjoyable, we propose a manga-specific image retrieval system. The proposed system consists of efficient margin labeling, edge orientation histogram feature description with screen tone removal, and approximate nearest-neighbor search using product quantization. For querying, the system provides a sketch-based interface. Based on the interface, two interactive reranking schemes are presented: relevance feedback and query retouch. For evaluation, we built a novel dataset of manga images, Manga109, which consists of 109 comic books of 21,142 pages drawn by professional manga artists. To the best of our knowledge, Manga109 is currently the biggest dataset of manga images available for research. Experimental results showed that the proposed framework is efficient and scalable (70 ms from 21,142 pages using a single computer with 204 MB RAM).
ISSN:	1380-7501 1573-7721