A Multi-faceted OCR Framework for Artificial Urdu News Ticker Text Recognition
Content based information search and retrieval has allowed for easier access to data. While Latin based scripts have gained attention and support from academia and industry, there is limited support for cursive script languages, like Urdu. In this paper, we present the first instance of Urdu news ticker detection and recognition and take a micron sized step towards the goal of super intelligence. The presented solution allows for automating the transcription, indexing and captioning of Urdu news video content. We present the first comprehensive data set, to our knowledge, for Urdu news ticker recognition, collected from 41 different news channels. The data set covers both high and low quality channels, distorted and blurred news tickers, making the data set an ideal test case for any automatic Urdu News Recognition system in future. We identify and address the key challenges in Urdu News Ticker text recognition …
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