Classification and Recognition of Gujarati Numeral using Nearest Neighbour Approach

Authors

  • Dr. Hetal R. Thaker  Department of M.C.A., Atmiya Institute of Technology & Science, Rajkot, Gujarat, India Department of M.C.A., Atmiya Institute of Technology & Science, Rajkot, Gujarat, India Department of M.C.A., Atmiya Institute of Technology & Science, Rajkot, Gujarat, India
  • Prof. Vivek J. Vyas  
  • Prof. Vaishali G. Sanghvi  

Keywords:

Gujarati numeral recognition, pattern recognition, artificial intelligence, pre-processing, nearest neighbour

Abstract

Optical Character Recognition is an area much explored since the beginning due to its wide range of applications. This paper focuses on optical Gujarati digit recognition. To recognize Gujarati digit certain set of operations like pre-processing is carried out. As a result of feature extraction vector of 9 elements is derived representing no. of connected neighbor pixels and last element presenting total of 8 elements. Classification repository is derived by applying pre-processing and feature extraction steps for each digit to create classification repository matrix of 10 X 9 size, where row represents Gujarati digit 0 to 9. To test this model image containing isolated Gujarati digit is given as input and the result of feature extraction vector is compared with last element of each row of classification repository matrix. If total matches then digit is recognized on the basis of index of the row. In case of similar total for two digits each element of vector is compared with row of classification repository matrix. Methodology, implementation of it and results obtained are presented in this paper.

References

  1. http://www.omniglot.com/writing/gujarati.htm
  2. K. Moro, M. Fakir, B. Dine, E. L. Kessab, B. Bouikhalene, and
  3. C. Daoui, “Gujarati handwritten numeral optical character through neural network and skeletonization,” vol. 3, no. 1, 2013.
  4. C. Patel, “Zone Identification for Gujarati Handwritten Word,” 2011.
  5. M. Maloo, K. V Kale, and I. Technology, “SUPPORT VECTOR MACHINE BASED GUJARATI NUMERAL,” Int. J., vol. 3, no. 7, pp. 2595–2600, 2011.
  6. A. R. Vasant, “Performance Evaluation of Different Image Sizes for Recognizing Offline Handwritten Gujarati Digits using Neural Network Approach,” in 2012 International Conference on Communication Systems and Network Technologies, 2012, pp. 271–274.
  7. M. Baheti, “Invariant Moments Approach for Gujarati Numerals,” no. 2, pp. 41–44, 2015.
  8. Mukesh M. Goswami,  Suman K. Mitra, “Offline handwritten Gujarati numeral recognition using low-level strokes”,   International Journal of Applied Pattern Recognition , volume 2  issue 4,  DOI: http://dx.doi.org/10.1504/IJAPR.2015.075955
  9. A. K. Sharma, D. M. Adhyaru, T. H. Zaveri and P. B. Thakkar, "Comparative analysis of zoning based methods for Gujarati handwritten numeral recognition," 2015 5th Nirma University International Conference on Engineering (NUiCONE), Ahmedabad, 2015, pp. 1-5. doi: 10.1109/NUICONE.2015.7449632
  10. R. Nagar and S. K. Mitra, "Feature extraction based on stroke orientation estimation technique for handwritten numeral," Advances in Pattern Recognition (ICAPR), 2015 Eighth International Conference on, Kolkata, 2015, pp. 1-6. doi: 10.1109/ICAPR.2015.7050654
  11. A. N. Vyas and M. M. Goswami, "Classification of handwritten Gujarati numerals," Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on, Kochi, 2015, pp. 1231-1237. doi: 10.1109/ICACCI.2015.7275781

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2016-06-30

Issue

Volume 2, Issue 3, May-June-2016

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. Hetal R. Thaker, Prof. Vivek J. Vyas, Prof. Vaishali G. Sanghvi, " Classification and Recognition of Gujarati Numeral using Nearest Neighbour Approach, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 3, pp.49-52, May-June-2016.