Effective video text detection using line features

Text superimposed on video frames provides synoptic or supplemental information on video semantics. In this paper, we propose a novel method to detect superimposed text effectively. First, we detect edges by an improved Canny edge detector. Then, a line-feature vector graph is generated based on the edge map and the stroke information is extracted. Finally text regions are generated and filtered according to line features. Experimental results show that, without much increasing the computational cost, our proposed method could suppress the false alarms notably. Furthermore, our method can be easily customized to applications with different tradeoffs in recall and precision.