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  Image Normalization and Preprocessing for Gujarati Character Recognition  
  Authors : Jayashree Rajesh Prasad
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Pattern recognition has been an important area in computer vision applications. In the case of a planar image, there are four basic forms of geometric distortion caused by the change in camera location: translation, rotation, scaling and skew. So far, a number of methods have been developed to solve these distortions, such as moment invariants’, Fourier descriptor, Hough transformation, shape matrix’ and the principle axis method. All of the above methods can be made invariant to translation, rotation and scaling. However, they become useless when pattern is skewed: when the direction of the camera or scanner is not vertical to the planar image or the sampling intervals in the x and y directions are not equal, the image is skewed. Authors present a moment based normalization process for character images for the purpose of enhancing the performance of character recognize for isolated characters of Gujarati. This paper focuses on character pre-processing and normalization stage of handwritten character recognition for Gujarati.


Published In : IJCSN Journal Volume 3, Issue 5

Date of Publication : October 2014

Pages : 334 - 339

Figures : 06

Tables : --

Publication Link : Image Normalization and Preprocessing for Gujarati Character Recognition




Jayashree Rajesh Prasad : graduated in Computer Science and Engineering from North Maharashtra University in 1996 and completed M.E. in Computer Engineering from Pune University in 2004. She pursued Ph.D. in Computer Science and engineering from Swami Ramananda Tirtha University, Nanded in 2014. She has a research project “Conversion of Gujarati Script to Speech”, funded by BCUD (University of Pune) to her credit. She works with Sinhgad College of Engineering, Pune. Her research interests are in the field of Soft Computing, pattern recognition and image processing. She is Life member of Computer Society of India, Life Member of Indian Society for Technical Education, Member of IAENG (International Association of Engineers) and Member of IACSIT (International Association of Computer Science and Information Technology).








Affine transformation






Author describes a normalization process that achieves invariance under affine geometric distortions. In this application authors apply a normalization procedure to the image so that it meets a set of predefined moment criteria. A recognition rate of 86.6 % [1] for the isolated characters of Gujarati is achieved. This paper does not focus on the classification details of this application. Author has focused on the moment based image normalization applied in the pre-prepossessing stage of a character recognition task.










[1] Jayashree Prasad, Uday Kulkarni, ‘Gujarati Character Recognition using weighted k-NN with mean chi square Distance Measure’, DOI 10.1007/s13042-013- 0187-z International Journal of Machine Learning and Cybernetics, Springer, ISSN 1868-8071. [2] M. Maloo and Kale, “Gujarati Script Recognition: A Review,” In: International Journal on Computer Science and Engineering (IJCSE), 2011. [3] A. Name, "Dissertation Title", M.S.(or Ph.D.) thesis, Department, University, City, Country, Year. [3] S. Antani and Lalitha Agnihotri, “Gujarati Character Recognition,” In: ICDAR, pp. 418-421, 1999. [4] Mohamed Cheriet, Nawwaf Harma, Cheng-Lin Liu, Ching Y. Sen, “Character Recognition Systems A Guide for Students and Practitioners,” A John Wiley & Sons, Inc., Publication, 2007. [5] Marius Bulacu, Lambert Schomaker and Axel Brink, “Text-Independent Writer Identification and Verification on Offline Arabic Handwriting,” In: ICDAR, IEEE Computer Society, Volume. II, pp. 769- 773, 2007. [6] Lam, L., Seong-Whan Lee, and Ching Y. Suen, Thinning Methodologies- A Comprehensive Survey, In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 14, No. 9, page 879, September 1992.