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Optical Character Recognition in the computering

ATEEQAH MOHAMMED ALI DARADI, ANCHIT SAJAL DHAR

Abstract


In today's world, advances in advanced scientific techniques drive more human communication limits in different areas of technology. One of these areas is the field of character recognition known as OKR. A simple way to store and remove in formation in these paper documents is in the computer system and then stores them as images. In this fast paced world there is a great need to digitize printed documents and document information directly in digital format. There is still a gap in this area today. OKR techniques continue to improvise from time to time in an effort to bridge this gap. This project is about developing the algorithm to recognize handwritten characters and also to identify images using neural networks. A new technique is proposed to identify images using artificial neural network schemes including feature extraction of characters and their implementation. It has been shown that the continued identification of characters through the network that more than 70% of the times.

Keywords: Neural network, character recognition, processing, technique

Cite this Article
Ateeqah Mohammed Ali Daradi, Anchit Sajal Dhar. Optical Character Recognition in the Computering. Journal of Software Engineering Tools & Technology Trends. 2018; 5(1): 1–5p.


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References


A. J. M. A. P. Bandara and N. G. J. Dias ( 2015 ) Optimizing Neural Network Architectures for Image Recognition Using genetic algorithms, international conference on advances in ICT for emerging regions (TCTER) : 84-88.

Ankit Sharma and Dipti R Chaudhary (2013) character recognition Using Neural Network, International journal of engineering Trends and Technology (IJETT). 4(4) : 2231.

Chand and Kumar (2014) Hand-Written Character recognition, department of electronics & commination engineering, nit Rourkela.

Jinfeng Bai, Zhineng Chen and Bailan Feng ( 2014 ) Image character recognition using DEEP convolutional neural network learned from different languages , IEEE .

Md. Iqbal Quraishi and J Pal (2012 ) Image Recognition and processing using Artificial Neural Network, 1st Int’l conf. on recent advances in information technology, RAIT.

Mohit Agarwal and Baijnath Kaushik ( 2015) Text recognition from image using Artificial Neural Network and genetic algorithm, International Conference on Green Computing and Internet of Things (ICGCIoT) ,IEEE , perceptron with one hidden layer.

Santaji Ghorpade, Jayshree Ghorpade and Shamla Mantri (2010) Pattern recognition using neural networks, international journal of computer science & information technology (IJCSIT),2(6).

Santosh Kumar Henge and B. Rama (2016) Comprative Study with Analysis of OCR Algorithms and Invention Analysis of Character Recognition Approched Methodologies,1st IEEE International Conference on Power Electronics. Intelligent Control and Energy Systems (ICPEICES).

Velappa Ganapathy and Charles C. H. Lean (2006) Optical Character Recognition Program for Images of printed text using a Neural Network, IEEE.

Yuk Ying Chung (1997) Neural network based image recognition system using geometrical moment, IEEE tencon - speech and Image technologies for computing and telecommunications.


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