A Novel Method for Sensing Obscene Videos using Scene Change Detection

Video scene change detection has great importance of managing and analyzing large amount of videos. Traditionally this technique used for indexing, segmenting and categorizing different types of videos. Very few works addressed to classify obscene using scene change detection method. In this research we proposed a simple approach for sensing objectionable videos by observing scene changes into different video genres. Video scenes are grouped into set of key frames. After analyzing duration of each scene and counting the number of key frames of designated scene, it has been shown that obscene videos have infrequent scene changing nature. While in sports, dramas, music and action films have large number of scene changes. We used six types of video genres and the decision has been made by setting a threshold based on extracted key frames. Experimental result showed that the accuracy is 83.33% and false positive rate is 16.67%.