Handwritten Malayalam Character Recognition using Regional Zone with Structural Features

  • Authors

    • Ajay James Government Engineering College, Thrissur
    • Raveena P V Government Engineering College, Thrissur
    • Chandran Saravanan NIT Durgapur
    2018-11-11
    https://doi.org/10.14419/ijet.v7i4.12551
  • Abstract

    Optical Character Recognition (OCR) tries to extract features from an image of script and converts to machine-readable code. OCR comprises of Line segmentation, Word segmentation, Character segmentation and Character Recognition. Printed documents are efficiently converted to the editable text format with 100% accuracy. Handwritten character recognition places difficulties in identifying and translating scripts because of the wide variation in human handwriting. Writing style including line spacing, word spacing, character sizes and shape of each character varies from person to person. Feature extraction and character recognition are different for different languages and become the most complicated task among the phases of OCR. By language characteristics, feature extraction can differ for each language. The Malayalam characters are characterized by their curved and noncursive nature. The handwritten character recognition for the Malayalam language that proposed here uses a regional zone based method with structural feature extraction.

  • References

    1. [1] Jia, Ashitta T., Yahkoob Ayappally, and K. Syama. â€Malayalam OCR: N-gram approach using SVM classifier.†In Advances in Computing, Communications, and Informatics (ICACCI), 2013 International Conference on, pp. 1799-1803. IEEE,2013.

      [2] Chaudhari, Shailesh A., and Ravi M. Gulati. â€An OCR for separation and identification of mixed English—Gujarati digits using kNN classifier.†In Intelligent Systems and Signal Processing (ISSP), 2013 International Conference on, pp. 190-193. IEEE,2013.

      [3] Mohand, Kamel Ait, Thierry Paquet, Nicolas Ragot, and Laurent Heutte. 2010 â€Structure Adaptation of HMM applied to OCR.â€In Pattern Recognition (ICPR), 2010 20th International Conference on, pp. 2877-2880. IEEE., 2010.

      [4] Panyam Narahari Sastry, T.R. Vijaya Lakshmi, N.V. Koteswara Rao, T.V. Rajinikanth, Abdul Wahab, 2014 â€Telugu Handwritten Character Recognition using Zoning Featuresâ€, IEEE, 2014


      [5] Blumenstein, Michael, Brijesh Verma, and Hasan Basli. 2003 â€A novel feature extraction technique for the recognition of segmented handwritten characters.†In Document Analysis and Recognition, 2003. Proceedings. Seventh International Conference on, pp. 137-141. IEEE 2003

      [6] Gayathri, P., and Sonal Ayyappan. 2014 â€Off-line handwritten character recognition using Hidden Markov Model.†In Advances in Computing, Communications, and Informatics ICACCI, 2014 International Conference on, pp. 518-523. IEEE.2014

      [7] Nisha Sharma, Bhupendra Kumar, Vandita Singh, 2014 â€Recognition of Offline Hand printed English Characters, Numerals and Special Symbols†5th International Conference, 2014.

      [8] Rajashekararadhya S. V, Vanaja Ranjan P, Manjunath Aradhya V N, 2008 â€Isolated Handwritten Kannada and Tamil Numeral Recognition: A Novel Approach,†First International Conference on Emerging Trends in Engineering and Technology IEEE. 2008

      [9] R. Giridharan, E. K. Vellingiriraj and P. Balasubramanie, "Identification of Tamil ancient characters and information retrieval from temple epigraphy using image zoning," 2016 International Conference on Recent Trends in Information Technology (ICRTIT), Chennai, 2016, pp. 1-7.

      [10] Dash, Kalyan Sourav, Niladri B. Puhan, and Ganapati Panda 2015 â€Handwritten numeral recognition using non-redundant Stockwell transform and bio-inspired optimal zoning.â€,IET Image Processing 9, no. 10 (2015): 874-882,2015.

      [11] Rajput, Ganpat Singh G., and Rajeshwari Horakeri 2013 â€Zone-based handwritten Kannada character recognition using crack code and SVM.†In Advances in Computing, Communications, and Informatics (ICACCI), 2013 International Conference on, pp. 1817-1821. IEEE, 2013.

      [12] Pirlo, Giuseppe, and Donato Impedovo 2012 â€Adaptive membership functions for handwritten character recognition by Voronoi-based image zoning.â€IEEE Transactions on Image Processing 21, no. 9 (2012): 3827-3837.

      [13] Manoj Kumar Mahto, Karamjit Bhatia R. K. Sharma,2015 â€Combined Horizontal and Vertical Projection Feature Extraction Technique for Gurmukhi Handwritten Character Recognition,†International Conference on Advances in Computer Engineering and Applications (ICACEA), 2015.

      [14] Rajesh Gopakumar, N V Subbareddy, KrishnamoorthiMakkithaya, U Dinesh Acharya, 2010 â€Zone-based Structural feature extraction for Script Identification from Indian Documents,†5th International Conference on Industrial and Information Systems, ICIIS,2010.

      [15] Kalyan S Dash, N. B. Puhan and Ganapati Panda,2014 â€A Hybrid Feature and Discriminant Classifier for High Accuracy Handwritten Odia Numeral Recognition,†IEEE Region 10 Symposium.

      [16] Aditya Raj, 2015 â€An Optical Character Recognition of Machine Printed Oriya Script,†Third International Conference on Image Information Processing.

      [17] Kartar Singh Siddharth, Mahesh Jangid, Renu Dhir, Rajneesh Rani, 2011â€Handwritten Gurmukhi Character Recognition Using Statistical and Background Directional Distribution Features,†International Journal on Computer Science and Engineering (0975-3397), Vol. 3, No. 6 June 2011.

      [18] Rafael M. O. Cruz, George D. C. Cavalcanti, and Tsang Ing Ren.†An Ensemble Classifier For Offline Cursive Character Recognition Using Multiple Feature Extraction Techniquesâ€, Neural Network(IJCNN) IEEE International Conference 2010.

      [19] U. Pal, T. Wakabayashi, and F. Kimura â€A System for Off-line Oriya Handwritten Character Recognition using Curvature Feature†10th International Conference on Information Technology.

      [20] Shanjana C, Ajay James, 2014 â€Offline Recognition of Malayalam Handwritten Text,†8th International Conference Interdisciplinary in Engineering, INTER-ENG 2014,9-10 October 2014.)

      [21] Karthika M, Ajay James, 2014 †A novel approach for Document image binarization using Bitplane slicing,†8th International Conference Interdisciplinary in Engineering, INTER-ENG 2014,9-10 October, Romania,2014

      [22] Primekumar K.P, Sumam Mary Idiculla â€Online Malayalam Handwritten Character Recognition using HMM and SVM,†International Conference on Signal Processing, Image Processing and Pattern Recognition [ICSIPRj]2013.

      [23] Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K M,â€SVM Based Feature Set Analysis in Dynamic Malayalam Handwritten Character Recognition†IEEE International Conference on Signal and Image Processing Applications (ICSIPA)2015.

      [24] Sk Md Obaidullah, Chayan Halder, Nibaran Das, Kaushik Roy, 2015 â€Indic Script Identification from Handwritten document Images An Unconstrained Block-level Approach,†IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS)2015

      [25] Pawan Kumar Singh, Aparajita Khan, Ram Sarkar, Mita Nasipuri, â€Identification from Multi-script Handwritten Documents,†Sixth International Conference on Computational Intelligence and communication networks.2014

      [26] Ashitta T, Jia Yahkoob Ayappally, Syama K,†Malayalam OCR: Ngram approach Using SVM Classierâ€, IEEE,2013

      [27] https://drive.google.com/drive/folders/0B1eLyjUeuERZWUVIOU9OZm40RHc

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  • How to Cite

    James, A., P V, R., & Saravanan, C. (2018). Handwritten Malayalam Character Recognition using Regional Zone with Structural Features. International Journal of Engineering & Technology, 7(4), 4629-4636. https://doi.org/10.14419/ijet.v7i4.12551

    Received date: 2018-05-07

    Accepted date: 2018-07-25

    Published date: 2018-11-11