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.
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Neumann, L., Matas, J. (2012). A Real-Time Scene Text to Speech System. In: Fusiello, A., Murino, V., Cucchiara, R. (eds) Computer Vision – ECCV 2012. Workshops and Demonstrations. ECCV 2012. Lecture Notes in Computer Science, vol 7585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33885-4_66
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DOI: https://doi.org/10.1007/978-3-642-33885-4_66
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