Email this article 
Open Access
Subscription or Fee Access
Digits and Special Character Recognition System using ANN and SNN Models
Abstract
The paper depicts pattern recognition of Digits and Special Character using Artificial Neural Network’s model Feed Forward Neural Network using Back Propagation Algorithm and Spiking Neural Network’s model Izhikevich Neuron model. Artificial Neural network is the second generation model and Spiking Neural Network is third generation model of Neural Networks. In this paper we have focused on recognizing the patterns and comparing the results of the two models Feed forward Neural Network and Izhikevich model by following the main steps of pattern recognition which are, Scanned handwritten Images, Pre-Processing of image, Feature Extraction of image, Training the network, Recognition/Classification of images.
Feed Forward Neural Network consists of three layers and this network is trained by Back propagation Algorithm. On the other hand, we have Izhikevich model which is well known for producing all known firing rates pattern. It is a combination of Hodgkin-Huxley model and computationally efficient Integrate-and Fire neuron model. Izhikevich model will recognize the input pattern of the image and generate the spikes. Using the above two models simulation results are obtained for recognition of digits and special characters and then comparing both models based on recognition rate, reliability, simulation time and number of neurons. We show that the Izhikevich model of spiking neural type provides improved performance.
Keywords
References
Mrs.Soni Chaturvedi, Rutika N.Titre, .A.Khurshid,"Review of Handwritten Pattern Recognition of Digits and Special Characters using Feed Forward Neural Network and Izhikevich Neuron Model”, IEEExplorer DOI-10.1109/ICESC-2014-83, INSPEC Acc.No 14111544 pp.[425-428].
Sumedha B. Hallale, Geeta D.Salunke, “Offline Handwritten Character Recognition: A Review”, International Journal of Advanced Computer and Mathematical Sciences, Vol 4, Issue 4, 2013,pp[250-256].
Arindam Basu, “Small-Signal Neural Models and Their Applications”, IEEE Transactions on Biomedical Circuits and systems, Vol 6, No.1, February 2012.
J. Pradeep, E.Srinivasan, S.Himavanthi, “Neural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten”, International Journal of Engineering Transactions B: Applications Vol. 25, No.2, May 2012.pp [99-106].
Binod Kumar Prasad and Goutam Sanyal, “A Model Approach to off-line English Character Recognition”, International Journal of Scientific and Research Publications, Vol 2, Issue 6, June 2012.
Nandish .M, Stafford Michahial, Hemanth Kumar P, Faizan Ahmed, “ Feature Extraction and Classification of EEG signal using Neural Network Based Techniques”, International Journal of Engineering and Innovative Technology Vol 2, Issue 4, October 2012.
B.Meftah O.Lezoray, S.Chaturvedi, A.Khurshid and A.Benvetton, “Image Processing with spiking Neural Network”, in Artificial Intelligence Evolutionary Computation and Metherusist, SC-427, Publisher Springer 2012.pp.[525-544].
Devinder Singh and Baljit Singh Khehra, “Digit Recognition System using Back Propagation Neural Network”, International Journal of Computer Science and Communication, Vol 2, No 1, January-June2011.pp [197-205].
Son Nobukawa, Haruhiko Nishimura, Teruya Yamanishi and Jian Qin Liu, “Signal Response Efficiency in Izhikevich Neuron Model”, SICE Annual Conference Waseda University, Tokyo, Japan September 2011.
Amit Kumar Gupta and Yash Pal Singh, “Analysis of Back Propagation of Neural Network Method in the String Recognition”, International Journal of Computer Theory and Engineering, Vol 3, No.5, October 2011.
Venkat Rangan, Abhishek Ghosh, Vladimir Aparin, Gert Cauwenberghs, “A Subthreshold a VLSI Implementation of the Izhikevich Simple Neuron Model”, 32nd Annual International Conference of the IEEE EMBS Buenos Aires, Argentina, August 31-September 4, 2010.
Roberto A. Vazquez, “Pattern Recognition using Spiking Neurons and Firing Rates”, IBERAMIA 2010, pp [423-432].
A. Rathinam and S.Padmini, “Security Assessment of Power System Using Artificial Neural Network- A Comparison between Euclidean Distances Based on Learning and Supervised Learning Algorithms”, International Conference on Computational Intelligence and Multimedia Applications 2007.
Eugene M.Izhikevich, “Which Model to use for Cortical Spiking Neurons?”, IEEE Transaction on Neural Networks Vol.15,No.5, September-2004.
Eugene M.Izhikevich, “Simple Model of Spiking Neurons”, IEEE Transactions on Neural Networks Vol.14, No.6, November 2003.
Albert Ali Shah, Ethen Alppaydine and Lale Akarin, “A Selective Attention- Based Method for Visual Patten Recognition with Application To Handwritten Digit Recognition and face Recognition”, IEEE Transactions on Pattern analysis and machine Intelligence Vol 24, No.3, March 2002.
R.Plamondon and S.N.Srihari, “On-line and Off-line handwritten Character recognition: A comprehensive survey”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, Vol.22, No.1, pp[63-84].
S.V.Rajashekararadhya, Dr.P.Vanaja Ranjan, “Efficient zone based Feature Extraction Algorithm for Handwritten Numeral Recognition of Four Popular South Indian Scripts”, Journal of Theoretical and Applied Information Technology, Vol 4, No.12.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.