Abstract
Handwriting recognition has always been an active and challenging research area with various applications in daily life and also in area of pattern recognition. Some of the applications are reading tool for blind people, reading handwritten bank cheques, by converting it into properly structured text which can be easily detected by the designed algorithms. This paper gives brief analysis of various handwritten recognition techniques, such as Optical Character Recognition (OCR), Artificial Neural Network (ANN), Intelligent Character Recognition (ICR), and Intelligent Word Recognition (IWR). Accuracy rates of all these methods were compared, and the comparative analysis demonstrates that OCR method is the best among them for the recognition of English handwritten characters. Merits and demerits are also discussed for the methods of recognition. Basic steps involved in the handwritten recognition process are also briefed.
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Tiwari, U., Jain, M., Mehfuz, S. (2019). Handwritten Character Recognition—An Analysis. In: Singh, S., Wen, F., Jain, M. (eds) Advances in System Optimization and Control. Lecture Notes in Electrical Engineering, vol 509. Springer, Singapore. https://doi.org/10.1007/978-981-13-0665-5_18
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DOI: https://doi.org/10.1007/978-981-13-0665-5_18
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