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.
“This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology (No.2010-0028046)”.
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Lee, J.H., Baik, S.W., Kim, K., Jung, C., Kim, W. (2011). IGC: An Image Genre Classification System. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23887-1_45
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DOI: https://doi.org/10.1007/978-3-642-23887-1_45
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