Handwritten Text Recognition using Machine Learning Techniques in Application of NLP
Polaiah Bojja1, Naga Sai Satya Teja Velpuri2, Gautham Kumar Pandala3, S D Lalitha Rao Sharma Polavarapu4, Pamula Raja Kumari5
1Professor, Polaiah Bojja*, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation.
2Pamula Raja Kumari, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation,
3Professor. Naga Sai Satya Teja Velpuri, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Educational Foundation.
4Gautham Kumar Pandala, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Educational Foundation.
5S D Lalitha Rao Sharma Polavarapu, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Educational Foundation.
Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 1394-1397 | Volume-9 Issue-2, December 2019. | Retrieval Number: A4748119119/2019©BEIESP | DOI: 10.35940/ijitee.A4748.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Handwriting Detection is a technique or ability of a Computer to receive and interpret intelligible handwritten input from source such as paper documents, touch screen, photo graphs etc. Handwritten Text recognition is one of area pattern recognition. The purpose of pattern recognition is to categorizing or classification data or object of one of the classes or categories. Handwriting recognition is defined as the task of transforming a language represented in its spatial form of graphical marks into its symbolic representation. Each script has a set of icons, which are known as characters or letters, which have certain basic shapes. The goal of handwriting is to identify input characters or image correctly then analyzed to many automated process systems. This system will be applied to detect the writings of different format. The development of handwriting is more sophisticated, which is found various kinds of handwritten character such as digit, numeral, cursive script, symbols, and scripts including English and other languages. The automatic recognition of handwritten text can be extremely useful in many applications where it is necessary to process large volumes of handwritten data, such as recognition of addresses and postcodes on envelopes, interpretation of amounts on bank checks, document analysis, and verification of signatures. Therefore, computer is needed to be able to read document or data for ease of document processing.
Keywords: E.G – For Example, NLP -Natural Language Processing, CNN – Convolutional Neural Network, OCR – Optical Character Recognition.
Scope of the Article: Natural Language Processing