Overlay Text Extraction From TV News Broadcast

TL;DR

This paper introduces a fast, threshold-free edge density method with contrast enhancement for overlay text detection, along with a novel tracking approach and OCR application, improving extraction accuracy in diverse TV news broadcasts.

Contribution

It presents a contrast enhancement preprocessing, a parameter-free edge density detection scheme, and a formalized multiple text region tracking method for overlay text extraction.

Findings

Superior performance on Indian TV news channels

Effective in varied text formats and animations

Robust text recognition with Tesseract OCR

Abstract

The text data present in overlaid bands convey brief descriptions of news events in broadcast videos. The process of text extraction becomes challenging as overlay text is presented in widely varying formats and often with animation effects. We note that existing edge density based methods are well suited for our application on account of their simplicity and speed of operation. However, these methods are sensitive to thresholds and have high false positive rates. In this paper, we present a contrast enhancement based preprocessing stage for overlay text detection and a parameter free edge density based scheme for efficient text band detection. The second contribution of this paper is a novel approach for multiple text region tracking with a formal identification of all possible detection failure cases. The tracking stage enables us to establish the temporal presence of text bands and their linking over time. The third contribution is the adoption of Tesseract OCR for the specific task of overlay text recognition using web news articles. The proposed approach is tested and found superior on news videos acquired from three Indian English television news channels along with benchmark datasets.