Neural network-based text location for news video indexing

Abstract

The retrieval of video clips from multimedia databases has been increasingly spotlighted. Texts in videos include useful information for automatic annotation or indexing. Text location is the first step for recognizing the textual information. This paper proposes a neural network-based text location method for news video indexing. Text can be characterized by texture, location, alignment, and font size. The proposed method classifies text pixels and non-text pixels using a network that operates as a set of texture discrimination filters. We find and locate text regions using histogram analysis after removing errors in the classification results. Experimental results show that the proposed method is effective at locating texts.