Viral transcript alignment

Gil Sadeh, Lior Wolf, Tal Hassner, Nachum Dershowitz, Daniel Stökl Ben Ezra

Abstract: We present an end-to-end system for aligning transcript letters to their coordinates in a manuscript image. An intuitive GUI and an automatic line detection method enable the user to perform an exact alignment of parts of document pages. In order to bridge large regions in between annotation, and augment the manual effort, the system employs an optical-flow engine for directly matching at the pixel level the image of a line of a historical text with a synthetic image created from the transcript's matching line. Meanwhile, by accumulating aligned letters, and performing letter spotting, the system is able to bootstrap a rapid semi-automatic transcription of the remaining text. Thus, the amount of manual work is greatly diminished and the transcript alignment task becomes practical regardless of the corpus size.