On-line Handwritten English Character Recognition Using Genetic Algorithm
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© - June Issue 2013 by IJCTT Journal|
|Volume-4 Issue-6 |
|Year of Publication : 2013|
|Authors :Shilpa Jumanal, Ganga Holi|
Shilpa Jumanal, Ganga Holi "On-line Handwritten English Character Recognition Using Genetic Algorithm "International Journal of Computer Trends and Technology (IJCTT),V4(6):1885-1890 June Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract: - Tremendous advancement in technology has produced varieties of electronics devices such as PDAs, handheld computers where non-keyboard based method of data entry are receiving more attention in the research communities and commercial sector. The most promising options are pen-based and voice-based inputs. The increase in usage of handheld devices which accepts handwritten input has created a growing demand for algorithm that can efficiently analyse and retrieve handwritten data. This paper proposed a methodology to recognize handwritten character written on the digitizing tablet. The proposed method is based on extraction of different spatial and temporal features from strokes of the character and recognition is done by using genetic algorithm algorithm as a tool to find an optimal subset of the stroke features. The proposed system is experimented on data set consisting of 5200 samples collected from various persons for English letters and recognition rate achieved is 83.1%.
. A. Shazia and Q. Aasia, “Document Image Processing - A Review,” International Journal of Computer Applications, November 2010, Volume 10, No.5.
. R. Plamondon and S. Srihari, “Online and off-line handwriting recognition: a comprehensive survey,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 63 –84.
. C. C. Tappert, C. Y. Suen and T. Wakahara, “The state of the art in online handwriting recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence,1990, pp. 787–808.
. A. Ashutosh , R. Rajneesh and RenuDhir, “ Handwritten Devanagari Character Recognition Using Gradient Features,” International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, Issue 5, May 2012.
. P. Chomtip, W. Verachad, J. Satheanpong and C. Nannaphat, “Thai Handwritten Character Recognition by Genetic Algorithm (THCRGA),” IACSIT International Journal of Engineering and Technology, Vol.3, No.2, April 2011.
. R. Plamondon, D. Lopresti, L.R.B. Shoemaker and R. Srihari, “On-line Handwriting Recognition,” Encyclopedia of Electrical and Electronics Eng., J.G. Webster, ed., vol. 15, pp. 123-146, New York: Wiley, 1999.
. X.Li, R.Plamondon, M.Parizeau, “Model-based on-line handwritten digit recognition,” Proc. of 14th Intl. Conf. On Pattern Recognition, Brisbane, Australia, August, 1998, pp.1134-1136.
. U. Pal, N. Sharma, T.Wakabayashi, and F.Kimura, "Off-line handwritten character recognition of Devanagari script," in Proc. 9th Conf. Document Analysis andRecognition, 2007, pp. 496-500.
. J. Sternby, J. Morwing, J. Anderson and C. Friberg, „„On-line Arabic handwriting recognition with templates,” Pattern Recognition, vol 42, 2009, pp. 3278-3286.
. I. Muthumani and C.R. Uma Kumari, “Online Character Recognition of Handwritten Cursive Script,” IJCSI International Journal of Computer Science Issues, vol. 9, Issue 3, No 2, 2012, pp. 352-354.
. D. Connell Scott, “On Line Handwritten Recognition Using Multiple Pattern Class Models,” Ph.D. Thesis, University de Michigan state, East Lansing, 2000.
. M. N. Anoop and K. J. Anil, “Online Handwritten Script Recognition,” IEEE transactions on pattern analysis and machine intelligence, vol. 26, no. 1, January 2004.
. L. Mahmoud, N. Sourour, B. Hala and M. A. Adel, “Genetic Algorithms for Perceptual Codes Extraction,” Journal of Intelligent Learning Systems and Applications, 2012, 4, 255-265
. F. L. Chung, T. C. Fu and R. W. P. Luk, “An Evolutionary Approach to Pattern-Based Time Series Segmentation,” IEEE transactions on evolutionary computation, Vol. 8, No. 5, 2004, pp. 471-489.
Keywords : On-line recognition, Genetic algorithm, spatial and temporal features, digital tablet.