IGC: an image genre classification system

Authors:
Joo Hwan Lee;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

In this paper, we present image genre classification system, called IGC. The proposed system categorizes images into one of three genres, such as art, photo, or cartoon images. The images features are extracted using standard MPEG-7 visual descriptors, after which they are trained using Neural Networks. The simulation results show that the proposed system successfully classifies images into correct classes with the rate of over 85% depending on the employed features.