Fast rotation-invariant video caption detection based on visual rhythm

Abstract

Text detection in images has been studied and improved for decades. There are many works that extend the existing methods for analyzing videos, however, few of them create or adapt approaches that consider inherent characteristics of videos, such as temporal information. This work proposes a very fast method for identifying video frames that contain text through a special data structure called visual rhythm. The method is robust to detect video captions with respect to font styles, color intensity, and text orientation. A data set was built in our experiments to compare and evaluate the effectiveness of the proposed method. © 2011 Springer-Verlag.