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A multiresolution optical character recognition (OCR) using neural networks is proposed for omnifont character recognition. It is motivated by the human reading process in which a low resolution is used to effectively process the majority of clean and unambiguous text, while a more complicated recognition scheme is invoked only when a high resolution is needed. Compared with the method that utilizes single resolution, the multiresolution system not only speeds up recognition by up to 20 times, but also improves accuracy of isolated character recognition from 99.8% to 99.9%. The multiresolution approach captures the essence of better reading, and provides the building blocks for the next-generation OCR systems.>
Wang et al. (Mon,) studied this question.