Video text extraction based on image regularization and temporal analysis

Video text extraction is the process of identifying embedded text on video, which is usually on complex background. This paper proposes a new approach to cope with this problem considering image regularization and temporal information. The former helps us to decrease the number of gray values in order to simplify the image content, and the second one takes advantage of video text persistence in order to identify video segments ignoring text changes. According to our experiments, the proposed method presents better results than other. Moreover, we propose a post-processing step for improving the text results obtained by Otsu method.