A novel low complexity TV video OCR system

Recent market report on Consumer Electronics shows that TV with Internet is going to be one of the most demanding products for the near future. As a consequence the demand of recognizing the TV context also increases among the research community. Lots of information about the TV video can be obtained from the meta data in case of digital TV broadcast. But in the developing countries like India, still the penetration of digital TV is only about 10%. So there is a need for video OCR system that can recognize the textual context of the TV video, since fair amount of contextual information can be obtained from the graphical text of the TV video. In this paper a low complexity video OCR system has been presented, that can be deployed on an embedded platform. The novelty of the proposed method is the use of low processing cycle and memory and yet getting a recognition accuracy of 84.23% which is higher than the usual video OCR recognition accuracy. Moreover, the proposed method can recognize about 180 characters on average per frame in 26.34 milliseconds.