A Comparative Approach for Overlay Text Detection and Extraction from Complex Video Scene

Abstract

Overlay text brings important semantic clues in
video content analysis such as video information retrieval and
summarization, since the content of the scene or the editors
intention can be well represented by using inserted text. Most of
the previous approaches to extracting overlay text from videos
are based on low-level features, such as edge, color, and texture
information. However, existing methods experience difficulties in
handling texts with various contrasts or inserted in a complex
background. In this paper, we propose a novel framework to
detect and extract the overlay text from the video scene. Based
on our observation that there exist transient colors between
inserted text and its adjacent background, a transition map is first
generated. Then candidate regions are extracted by a reshaping
method and the overlay text regions are determined based on
the occurrence of overlay text in each candidate.
In this paper represents comparative approach between edge and
change in intensity models that are computationally fast and
invariant to basic transformations like horizontal, Vertical and
scaling. We demonstrate that change in intensity context can be
used to detect overlay text regions. Intensity context describes all
boundary points of the shape with respect to any single boundary
point.