Text extraction in MPEG compressed video for content-based indexing

Video text extraction is a core technique for multimedia applications such as news-on-demand (NOD) and digital libraries, and research about video text extraction have been conducted vigorously. In this paper, we propose an efficient method for extracting texts in MPEG compressed videos for content-based indexing. The proposed method makes the best use of 2-level DCT coefficients and macroblock type information in MPEG compressed video, and this method can be organized into three stages to increase overall performance; text frame detection, text region extraction, and character extraction. The main advantage of the proposed method is that it can avoid the overhead of decompressing video into individual frames in the pixel domain. We evaluated this method using various types of news video data