Fast Text Matching in Digital Videos

This paper proposes a fast and reliable video text matching algorithm suitable to tracking and locating text in given videos. The core of the algorithm relies on using fast cross-correlation and pyramid down-sampling techniques in a coarse-to-fine scheme. Fast local correlation, referred to as single matching phase, is achieved by using recursive computation schemes, which enabled us to minimize the amount of calculations required at every new pixel. By working with rectangular sub-images, which obtained by segmenting the frames at different levels of the pyramid, the speed of the algorithm can be increased and the intermediate memory storage requirement is reduced. We have tested our match algorithm in a large set of experiments with video clips recorded from television and achieved good matching results.