OCR Recognition System for Degraded Urdu and Devnagari Script

Any Optical character Recognition System has to undergo Pre-processing, Segmentation and classification to change the image into machine editable form. In this paper algorithm for Neural Network is applied for the recognition of Urdu and Devanagari Characterts. In all the phases segmentation plays an important role in character Recognition System. By applying the algorithm we can see that the system is able to recognize characters of Urdu and Devanagari Scripts. The result obtained are compared with other methods to prove that this method is better from others.

[1]  Andreas Keller,et al.  Lexicon-free handwritten word spotting using character HMMs , 2012, Pattern Recognit. Lett..

[2]  Sanjay Kumar,et al.  A REVIEW ON RECOGNITION OF HANDWRITTEN URDU CHARACTERS USING NEURAL NETWORKS , 2017 .

[3]  Dante Mújica-Vargas,et al.  Block-Matching Fuzzy C-Means clustering algorithm for segmentation of color images degraded with Gaussian noise , 2018, Eng. Appl. Artif. Intell..

[4]  Panu Somervuo,et al.  How to make large self-organizing maps for nonvectorial data , 2002, Neural Networks.

[5]  Muhammad Imran Razzak,et al.  Urdu Nasta’liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks , 2016, SpringerPlus.

[6]  Amit Choudhary,et al.  Off-line Handwritten Character Recognition Using Features Extracted from Binarization Technique☆ , 2013 .

[7]  Shahrokh Heidari,et al.  A novel quantum binary images thinning algorithm: A quantum version of the Hilditch's algorithm , 2017 .

[8]  Muhammad Waqas Anwar,et al.  Printed Urdu Nastalique Script Recognition Using Analytical Approach , 2015, 2015 13th International Conference on Frontiers of Information Technology (FIT).

[9]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[10]  D. E. Rumelhart,et al.  Learning internal representations by back-propagating errors , 1986 .

[11]  M. M. Farhad,et al.  An efficient Optical Character Recognition algorithm using artificial neural network by curvature properties of characters , 2014, 2014 International Conference on Informatics, Electronics & Vision (ICIEV).

[12]  Prasenjit Dey,et al.  HMM-based Indic handwritten word recognition using zone segmentation , 2016, Pattern Recognit..

[13]  IMRAN KHAN PATHAN,et al.  Recognition of Offline Handwritten Isolated Urdu Character , 2012 .

[14]  Umapada Pal,et al.  A comparative study of features for handwritten Bangla text recognition , 2015, 2015 13th International Conference on Document Analysis and Recognition (ICDAR).

[15]  Inam Shamsher,et al.  Urdu compound Character Recognition using feed forward neural networks , 2009, 2009 2nd IEEE International Conference on Computer Science and Information Technology.

[16]  Prabhat Kumar,et al.  RNN based online handwritten word recognition in Devanagari and Bengali scripts using horizontal zoning , 2019, Pattern Recognit..

[17]  Sarmad Hussain,et al.  Urdu computing standards: Urdu Zabta Takhti (UZT) 1.01 , 2001, Proceedings. IEEE International Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Century..

[18]  Yambem Jina Chanu,et al.  Image Segmentation Using K -means Clustering Algorithm and Subtractive Clustering Algorithm , 2015 .

[19]  Awais Adnan,et al.  OCR For Printed Urdu Script Using Feed Forward Neural Network , 2007 .