Content based cartoon video classification using Dynamic Thepade's Ternary Block Truncation Coding (DTTBTC)

Content Based Video Classification is becoming necessary for various video analysis applications to be able to handle humongous amounts of video data being generated & shared all over the Internet. This paper proposes use of DTTBTC for color based feature extraction from video key frames which are used by machine learning classifiers for training & testing. Experimental results show accuracy of video classification using combinations of color spaces, classifiers & data pre-processing techniques.