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Reseach Article

Handwritten Manuscript Digitizer

by Kaushil Ruparelia, Ashay Shah, Seema Wadhwani, M. Mani Roja
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 6
Year of Publication: 2016
Authors: Kaushil Ruparelia, Ashay Shah, Seema Wadhwani, M. Mani Roja
10.5120/ijca2016908467

Kaushil Ruparelia, Ashay Shah, Seema Wadhwani, M. Mani Roja . Handwritten Manuscript Digitizer. International Journal of Computer Applications. 136, 6 ( February 2016), 24-27. DOI=10.5120/ijca2016908467

@article{ 10.5120/ijca2016908467,
author = { Kaushil Ruparelia, Ashay Shah, Seema Wadhwani, M. Mani Roja },
title = { Handwritten Manuscript Digitizer },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 6 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 24-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number6/24158-2016908467/ },
doi = { 10.5120/ijca2016908467 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:36:20.670797+05:30
%A Kaushil Ruparelia
%A Ashay Shah
%A Seema Wadhwani
%A M. Mani Roja
%T Handwritten Manuscript Digitizer
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 6
%P 24-27
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In India, there are various instances where information is gathered by filling a questionnaire or a form. This information is then updated manually into the databases by the concerned authorities. Due to manual data entry, human error results in the capture of inaccurate data and thereby results in faulty storage and analysis of the data. The process is time consuming with a greater probability of error. This document serves as a guideline to automate and expedite the above process. The paper contains ideas of converting the handwritten samples into electronic data. It uses the kernel method of Multi class Support Vector Machine for handwritten character recognition. The data is first extracted in form of individual images for the corresponding data field, pre processed and converted to digital format. This reduces the time and human effort needed for the same. This paper aims at easing the process of evaluation by automating the correction process.

References
  1. Nasien, Dewi, Habibollah Haron, and Siti Sophiayati Yuhaniz, The Study of Handwriting Character Recognition (HCR) and Support Vector Machine (SVM), (439-447)
  2. Fabien Lauer, Ching Y. Suen, G´erard Bloch. A trainable feature extractor for handwritten digit recognition. Pattern Recognition, Elsevier, 2007, 40 (6), pp.1816-1824. <10.1016/j.patcog.2006.10.011>
  3. Character Recognition Using Matlab’s Neural Network Toolbox Kauleshwar Prasad, Devvrat C. Nigam, Ashmika Lakhotiya and Dheeren Umre International Journal of u- and e- Service, Science and Technology Vol. 6, No. 1, February, 2013(13-20)
  4. OCR binarization and image pre-processing for searching historical documents Maya R. Gupta∗, Nathaniel P. Jacobson, Eric K. Garcia 40 (2007) 389 – 397
  5. N. Otsu, A threshold selection method from gray-level histograms, IEEE Trans. Systems Man Cybernet Vol. 1, January 1979 (62-66).
  6. M. H. Shakoor and F. Tajeripour, Circular Mean Filtering For Textures Noise Reduction, Iranian Journal of Electrical & Electronic Engineering, Vol. 11, No. 3, Sep. 2015
  7. Handwritten Character Recognition Using Multiclass SVM Classification with Hybrid Feature Extraction Muhammad Naeem Ayyaz 1, Imran Javed 2 and Waqar Mahmood 3 Pak. J. Engg. & Appl. Sci. Vol. 10, Jan., 2012 (57-67)
  8. Shubhangi D. C., Prof. P.S. Hiremath, Handwritten English Character And Digit Recognition Using Multiclass SVM Classifier And Using Structural Micro Features, International Journal of Recent Trends in Engineering, Vol 2, No. 2, November 2009, (193-195)
Index Terms

Computer Science
Information Sciences

Keywords

HCR OCR Support Vector Machine Kernel trick.