Recognition and Filtration of Unwanted Video-Sequences

The thesis deals with the possibilities of recognition video sequences and possibility of machine learning based on previous knowledge. I use neural networks which I learn on characteristics generated from images. Images are characterized using image functions like histogram and statistical functions such as mean and correlations to detect scenes in video-sequence. I used all of these findings to implement the demonstration program. The program can play video, display statistical information about the sequence or frame by frame and detect sequences similar to advertisements on the basis of statistical properties and respond to it by defined events