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A Real-Time Scene Text to Speech System
Lukáš Neumann and Ji
í Matas
neumalu1@cmp.felk.cvut.cz
matas@cmp.felk.cvut.cz
http://textspotter.felk.cvut.cz/
Abstract. An end-to-end real-time scene text localization and recognition method is demonstrated. The method localizes textual content in images, a video or a webcam stream, performs character recognition (OCR) and “reads” it out loud using a text-to-speech engine. The method has been recently published, achieves state-of-the-art results on public datasets and is able to recognize different fonts and scripts including non-latin ones.
The real-time performance is achieved by posing the character detection problem as an efficient sequential selection from the set of Extremal Regions (ERs) which has a linear computation complexity in the number of pixels in the image. Robustness to blur, noise and illumination and color variations is also demonstrated. Finally, we show effects of various control parameters.
LNCS 7585, p. 619 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012