A cartoon image classification system using MPEG-7 descriptors

Authors:
Junghyun Kim;Sung Wook Baik;Kangseok Kim;Changduk Jung;Wonil Kim
Affiliations:
College of Electronics and Information Engineering at Sejong University, Seoul, Korea;College of Electronics and Information Engineering at Sejong University, Seoul, Korea;Department of Knowledge Information Security at Ajou University, Suwon, Korea;Department of Computer and Information Science at Korea University, Korea;College of Electronics and Information Engineering at Sejong University, Seoul, Korea
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
Year:
2011

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Abstract

Today cartoon images take more portion of digital multimedia than ever as we notice this phenomenon in the entertainment business. With the explosive proliferation of cartoon image contents on the Internet, we seem to need a classification system to categorize these cartoon images. This paper presents a new approach of cartoon image classification based on cartoonists. The proposed cartoon image classification system employs effective MPEG-7 descriptors as image feature values and learns features of particular cartoon images, and classifies the images as multiple classes according to each cartoonist. In the performance simulation we evaluate the effectiveness of the proposed system on a large set of cartoon images and the system successfully classifies images into multiple classes with the rate of over 90%.