Robust Text Stroke Extraction from Video

In this paper, we present a novel approach which employs the temporal redundancy of video texts to improve the performance of text segmentation and stroke extraction from complex background. We first demonstrate how to obtain the required aligned text image sequences from video frames via a robust corners-set matching scheme. Then the changing background pixels can be identified and removed by exploiting the statistics of the temporal redundancy of video. The text stroke pixels can be clearly separated from the complex background. Experiments on TV programs and movies videos show the proposed approach can generate clean text strokes image which can efficiently improve the OCR's performance compare to some traditional approaches.