Comic image category classification using local features

Authors:
Yusuke In;Nakamura Kentaro;Masakazu Higuchi;Jonah Gamba;Atushi Koike;Hitomi Murakami
Affiliations:
Information Science, Seikei University, Tokyo;Information Science;Information Science, Seikei University;Information Science, Seikei University;Information Science, Seikei University;Information Science, Seikei University
Venue:
CSCS '11 Proceedings of the 2nd international conference on Circuits, systems, control, signals
Year:
2011

Citing 3
Cited 0

Digital Imaging: Theory and Applications, with CD-ROM

Digital Imaging: Theory and Applications, with CD-ROM
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Real-time line detection through an improved Hough transform voting scheme

Pattern Recognition

Quantified Score

Hi-index	0.01

Visualization

Abstract

Due to the recent development of the information society, there are many multimedia data on the Web. Especially in Japan, there are various kinds of comic images on the Web, but effective methods of searching for the category classification are not present. The need for a system that stores and manages image content will clearly increase in the future. In this paper, we propose a system for category classification of comic images and evaluate it s performance experimentally.