Automatic identification of text in digital video key frames

Scene and graphic text can provide important supplemental index information in video sequences. In this paper we address the problem automatically identifying text regions in digital video key frames. The text contained in video frames is typically very noisy because it is aliased and/or digitized at a much lower resolution than typical document images, making identification, extraction and recognition difficult. The proposed method is based on the use of a hybrid wavelet/neural network segmenter on a series of overlapping small windows to classify regions which contain text. To detect text over a wide range of font sizes, the method is applied to a pyramid of images and the regions identified at each level are integrated.