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Rajan Transform Based Spectral Analysis of Handwritten Characters

Received: 18 May 2016     Accepted: 12 June 2016     Published: 11 July 2016
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Abstract

Homomorphic transforms are better suited for pattern recognition or classification. In general, homomorphic maps are not invertible and hence they are known as transformations. So, they do not fall under the category of mathematical transforms. But if the inverse of a transformation is obtained using an algorithm or a semi-decision procedure the transformation could be called a transform in the loose sense. Nonlinear homomorphic operators are not meant for analysis and synthesis, but they are used for classification. In this context, efforts were made to search for a homomorphic map which could be examined for character recognition. One such nonlinear homomorphic map has been identified as Rajan Transform. This paper provides details of this transform and its working principle in recognition of handwritten characters.

Published in American Journal of Networks and Communications (Volume 5, Issue 3)
DOI 10.11648/j.ajnc.20160503.12
Page(s) 60-67
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Rajan Transform, Hadamard Transform, Homomorphic Transform

References
[1] Rajan, E. G., ‘Symbolic Computing, Signal and Image Processing’, Anshan Publications, 6 Newlands Road, Tunbridge Wells, Kent TN4 9AT, United Kngdom, 2003.
[2] Rajbala Tokas & Aruna, B 2012, ‘A comparative analysis of feature extraction techniques for handwritten character recognition’, International Journal of Advanced Technology and Engineering Research, vol. 2, no. 4, pp. 215-219.
[3] Amritha Sampath, Tripti, C & Govindaru V 2012, ‘Freeman code based off-line handwritten character recognition for Malayalam using Back propagation neural networks’, Advance computing: An international journal, vol. 3, no. 4, pp. 51-58.
[4] Ashutosh, A, Rajneesh Rani & Renu Dhir 2012, ‘Handwritten Devanagari Character Recognition Using Gradient Features’, International Journal of Advanced Research in Computer Science and Software Engineering, vol. 2, no. 5, pp. 85-90.
[5] Rajib Lochan Das, Binod Kumar Prasad & Goutam Sanyal 2012, ‘HMM based Offline Handwritten Writer Independent English Character Recognition using Global and Local Feature Extraction’, International Journal of Computer Applications (0975 - 8887), vol. 46, no. 10, pp. 45-50.
[6] Ashok, Jammi & Rajan, EG 2011, ‘Off-Line Hand Written Character recognition using Radial Basis Function’, in International Journal of Advanced Networking and Applications (IJANA), vol. 2, no. 4, pp. 792-795.
[7] Aiquan Yuan, Gang Bai, Lijing Jiao & Yajie Liu 2012, ‘Off-line Handwritten English Character Recognition based on Convolutional nneural network’, Document Analysis Systems (DAS), 2012 10th IAPR International Workshop, vol., no., pp. 125, 129.
[8] Alam, FI & Banik, B ‘Off-line isolated bangla handwritten character recognition using spatial relationships,’ Informatics, Electronics & Vision (ICIEV), 2013 International Conference on, vol., no., pp. 1,6, 17-18 May 2013
[9] Ekambaram Naidu, M & Rajan, E G 2009, ‘Rajan Transform and its uses in Pattern Recognition’, Informatica, vol. 33, pp. 213-220.
[10] Ashok, Jammi & Rajan, EG 2012, ‘Robust Technique based Off-Line Hand Written Character recognition’, European Journal of Scientific Research, vol. 84, no. 1.
[11] Rajan, E G, ‘On the Notion of Generalized Rapid Transformation’, World multi conference on Systemics, Cybernetics and Informatics, Caracas, Venezuela, July 7-11, 1997
[12] Rajan, EG 1993, ‘Cellular Logic Array Processing Techniques for High- Throughput Image Processing Systems’, Invited paper, Sadhana, Special Issue on Computer Vision, The Indian Academy of Sciences, vol. 18, pp. 279-300.
[13] Rajan, EG 1996, On the Notion of a Geometric Filter and its relevance in the neighborhood processing of digital images in hexagonal grids, Fourth International Conference on Control, Automation, Robotics and Vision, Westin Stamford, Singapore, organized by the Nanyand Technological University, Singapore.
[14] Rajan, EG 2003, ‘Symbolic Computing – Signal and Image Processing’, B. S. Publications, Hyderabad.
[15] Wanli Ouyang & Cham, WK ‘Fast algorithm for Walsh Hadamard Transform on sliding windows’, pattern analysis and machine intelligence, IEEE Transactions, vol. 32, no. 1.
[16] Whah, S, Kumar, G & Govindaraju, V 2012, ‘Multilingual word spotting in offline handwritten documents,’ Pattern Recognition (ICPR), 2012 21st International Conference, pp. 310, 313.
[17] Helger Lipmaa 2002, ‘On Differential Properties of Pseudo-Hadamard Transform and Related Mappings’, INDOCRYPT 2002, LNCS 2551.
Cite This Article
  • APA Style

    Jammi Ashok, Kuntigorla Saidulu, Bayisa Taye Mulatu. (2016). Rajan Transform Based Spectral Analysis of Handwritten Characters. American Journal of Networks and Communications, 5(3), 60-67. https://doi.org/10.11648/j.ajnc.20160503.12

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    ACS Style

    Jammi Ashok; Kuntigorla Saidulu; Bayisa Taye Mulatu. Rajan Transform Based Spectral Analysis of Handwritten Characters. Am. J. Netw. Commun. 2016, 5(3), 60-67. doi: 10.11648/j.ajnc.20160503.12

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    AMA Style

    Jammi Ashok, Kuntigorla Saidulu, Bayisa Taye Mulatu. Rajan Transform Based Spectral Analysis of Handwritten Characters. Am J Netw Commun. 2016;5(3):60-67. doi: 10.11648/j.ajnc.20160503.12

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  • @article{10.11648/j.ajnc.20160503.12,
      author = {Jammi Ashok and Kuntigorla Saidulu and Bayisa Taye Mulatu},
      title = {Rajan Transform Based Spectral Analysis of Handwritten Characters},
      journal = {American Journal of Networks and Communications},
      volume = {5},
      number = {3},
      pages = {60-67},
      doi = {10.11648/j.ajnc.20160503.12},
      url = {https://doi.org/10.11648/j.ajnc.20160503.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.20160503.12},
      abstract = {Homomorphic transforms are better suited for pattern recognition or classification. In general, homomorphic maps are not invertible and hence they are known as transformations. So, they do not fall under the category of mathematical transforms. But if the inverse of a transformation is obtained using an algorithm or a semi-decision procedure the transformation could be called a transform in the loose sense. Nonlinear homomorphic operators are not meant for analysis and synthesis, but they are used for classification. In this context, efforts were made to search for a homomorphic map which could be examined for character recognition. One such nonlinear homomorphic map has been identified as Rajan Transform. This paper provides details of this transform and its working principle in recognition of handwritten characters.},
     year = {2016}
    }
    

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    T1  - Rajan Transform Based Spectral Analysis of Handwritten Characters
    AU  - Jammi Ashok
    AU  - Kuntigorla Saidulu
    AU  - Bayisa Taye Mulatu
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    T2  - American Journal of Networks and Communications
    JF  - American Journal of Networks and Communications
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    AB  - Homomorphic transforms are better suited for pattern recognition or classification. In general, homomorphic maps are not invertible and hence they are known as transformations. So, they do not fall under the category of mathematical transforms. But if the inverse of a transformation is obtained using an algorithm or a semi-decision procedure the transformation could be called a transform in the loose sense. Nonlinear homomorphic operators are not meant for analysis and synthesis, but they are used for classification. In this context, efforts were made to search for a homomorphic map which could be examined for character recognition. One such nonlinear homomorphic map has been identified as Rajan Transform. This paper provides details of this transform and its working principle in recognition of handwritten characters.
    VL  - 5
    IS  - 3
    ER  - 

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Author Information
  • School of Electrical and Computer Engineering, Hawassa University, Hawassa, Ethiopia

  • School of Electrical and Computer Engineering, Hawassa University, Hawassa, Ethiopia

  • School of Electrical and Computer Engineering, Hawassa University, Hawassa, Ethiopia

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