Text Detection, Localization and Segmentation in Compressed Videos

Abstract

Video text information plays an important role in semantic-based video analysis, indexing and retrieval. Video texts are closely related to the content of a video. Text-based video analysis, browsing and retrieval are usually carried out in the following for steps: video text detection, localization, segmentation and recognition. Videos are commonly stored in compressed formats where MPEG coding techniques are adopted. In this paper, a DCT coefficient based multilingual video text detection and localization scheme for compressed videos is proposed. Candidate text blocks are detected in terms of block texture constraint. An adaptive method for the horizontal and vertical aligned text lines determination is then designed according to the run length of the horizontal and vertical block numbers. The remaining block regions are further verified by local block texture constraints. And the text block region can be localized by virtue of the horizontal and vertical block texture projections. Finally, a foreground and background integrated (FBI) video text segmentation approach is adopted in this paper to eliminate the complex background in text regions. The final experimental results show the effectiveness of our methods.