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Optical Character Recognition using Neural Network

K. S. Bhavana, B. Pruthvi Raj, C. Sushmitha, S. Sushmitha


Character Recognition (CR) has always been an active research field in the past and is still a challenging research topic due to its wide range of applications. The most important methods of offline handwriting recognition can be divided into two categories: overall and segmentation- based.

When considering the global features extracted from the complete word image, the holistic method is used when recognizing limited vocabulary. On the other hand, the segment-based strategy uses a bottom-up approach, starting at the line or symbol level, and processing meaningful words. After segmentation, the problem comes down to recognizing a single character or line. Therefore, the system can use unlimited vocabulary.

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