Time Efficient Approach To Offline Hand Written Character Recognition Using Associative Memory Net

In this paper, an efficient Offline Hand Written Character Recognition algorithm is proposed based on Associative Memory Net (AMN). The AMN used in this work is basically auto associative. The implementation is carried out completely in 'C' language. To make the system perform to its best with minimal computation time, a Parallel algorithm is also developed using an API package OpenMP. Characters are mainly English alphabets (Small (26), Capital (26)) collected from system (52) and from different persons (52). The characters collected from system are used to train the AMN and characters collected from different persons are used for testing the recognition ability of the net. The detailed analysis showed that the network recognizes the hand written characters with recognition rate of 72.20% in average case. However, in best case, it recognizes the collected hand written characters with 88.5%. The developed network consumes 3.57 sec (average) in Serial implementation and 1.16 sec (average) in Parallel implementation using OpenMP.

[1]  Tetsushi Wakabayashi,et al.  Handwritten Numeral Recognition of Six Popular Indian Scripts , 2007 .

[2]  Hafiz Imtiaz,et al.  A Wavelet-Domain Local Dominant Feature Selection Scheme for Face Recognition , 2012 .

[3]  Ashish Chaturvedi,et al.  Neural Networks for Handwritten English Alphabet Recognition , 2012, ArXiv.

[4]  S. Himavathi,et al.  Diagonal Based Feature Extraction for Handwritten Alphabets Recognition System using Neural Network , 2011, ArXiv.

[5]  Ching Y. Suen,et al.  Historical review of OCR research and development , 1992, Proc. IEEE.

[6]  N Manivannan,et al.  Optical correlator-neural network hybrid system for many patterns recognition , 2010, IEEE 8th International Symposium on Intelligent Systems and Informatics.

[7]  Yafang Xue,et al.  Optical Character Recognition , 2022 .

[8]  D. Singh,et al.  Handwritten English Character Recognition Using Neural Network , 2010 .

[9]  Subhadip Basu,et al.  Handwritten Bangla Alphabet Recognition using an MLP Based Classifier , 2012, ArXiv.

[10]  S. Impedovo,et al.  Optical Character Recognition - a Survey , 1991, Int. J. Pattern Recognit. Artif. Intell..

[11]  Chuanjun Liu,et al.  A Recognition Algorithm for Chinese Chararcter Based on Minimum Distance Classifier , 2009, 2009 Second International Workshop on Computer Science and Engineering.

[12]  Tonglin Zhu,et al.  The Research of Algorithm for Handwritten Character Recognition in Correcting Assignment System , 2011, 2011 Sixth International Conference on Image and Graphics.

[13]  S. N. Sivanandam,et al.  Principles of soft computing , 2011 .