Artificial Immune System Based Recognition of Handwritten Kannada Numerals

Abstract:

Artificial immune system (AIS) based classification approach is relatively new in the field of pattern recognition (PR). The capability of AIS for learning new information, recalling what has been learned and recognizing a decentralized pattern are reasons why numerous models have been developed, implemented and used in various types of problems. This paper explores this paradigm in the context of recognition of handwritten Kannada numerals. In this paper, the AIS is used for training the extracted features of handwritten Kannada numerals. Zonal based feature extraction algorithm is being used and K-Nearest Neighbor (K-NN) classifier is used for classification. The performance of the proposed algorithm has been investigated in detail on nearly 1250 samples of Handwritten Kannada Numerals and an recognition accuracy of 98.11% has been obtained.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 900-906
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.900
• Online since: January 2012
• Authors: H.R. Mamatha, Murthy K. Srikanta, K.S. Amrutha, P. Anusha, R. Azeemunisa
• Keywords: Artificial Immune Systems (AIS), Kannada Handwritten Numeral, K-NN Classifier, OCR

References

[1] J. Timmis: Artificial Immune Systems: a novel data analysis techniques inspired by the immune network theory, PhD Thesis, University of Wales, Aberystwyth, (2001).

[2] D. Dasgupta: An overview of artificial immune systems and their applications, In Artificial Immune Systems and Their Applications, Springer (1998), pp.3-21.

DOI: 10.1007/978-3-642-59901-9_1

[3] A.B. Watkins: AIRS: A Resource Limited Artificial Immune Classifier, Master's dissertation, Dept. of Computer Science, Mississippi State University, (2001).

[4] J.H. Cater: The Immune System as A Model for Pattern Recognition and Classification, " vol. 7 (1) of Journal of the American Medical Informatics Association (2000), pp.28-41.

[5] Liana M. Lorigo and Venu Govindaraju: Offline Arabic handwriting recognition: A Survey, vol. 22, no. 5 of IEEE Transactions on Pattern Analysis and Machine Intelligence (2006), pp.712-724.

DOI: 10.1109/tpami.2006.102

[6] Nafiz. Arica and Fatos T. Yarman-Vural: An Overview of character recognition focused on off-line handwriting', vol. 31, no. 2 of IEEE Transactions on System, Man, Cybernetics-Part C: Applications and Reviews(2001), pp.216-233.

DOI: 10.1109/5326.941845

[7] R. Plamondon and S. N. Srihari: On-line and Off-line Handwritten Character Recognition: A Comprehensive Survey, vol. 22, no. 1 of IEEE. Transactions on Pattern Analysis and Machine Intelligence (2000), pp.63-84.

DOI: 10.1109/34.824821

[8] G. Nagy: Chinese Character Recognition, A Twenty Five Years Retrospective, In Proceedings of International Conference on Pattern Recognition (1988), pp.109-114.

DOI: 10.1109/icpr.1988.28196

[9] U. Pal and B.B. Chaudhuri: Indian Script Character Recognition: A Survey, Vol. 37 of Pattern Recognition (2004), pp.1887-1899.

DOI: 10.1016/j.patcog.2004.02.003

[10] M. Abdul Rahiman , M. S. Rajasree: A Detailed Study and Analysis of OCR Research in South Indian Scripts, In the International Conference on Advances in Recent Technologies in Communication and Computing (2009), pp.31-38.

DOI: 10.1109/artcom.2009.45

[11] G. G. Rajput and S. M. Mali: Fourier descriptor based Isolated Marathi Handwritten numeral Recognition, In the International Journal of Computer Application (2010), p.5120/724-1017.

DOI: 10.5120/724-1017

[12] S.V. Rajashekararadhya, and P. Vanaja Ranjan: Handwritten Numeral Recognition of Three Popular South Indian Scripts: A Novel Approach, In the Proceedings of the Second International Conference on Information Processing(2008), pp.162-167.

DOI: 10.1109/tencon.2008.4766450

[13] T. Wakabayashi, U. Pal, F. Kimura and Y. Miyake: F-ratio Based Weighted Feature Extraction for Similar Shape Character Recognition, In the Proceedings of the 10th International Conference on Document Analysis and Recognition(2009), pp.456-460.

DOI: 10.1109/icdar.2009.197

[14] Utpal Garain, M. P. Chakraborty, and D. Dutta Majumder: Improvement of OCR Accuracy by Similar Character Pair Discrimination: an Approach based on Artificial Immune System, Vol. 2 of the Proceedings of the 18th International Conference on Pattern Recognition (2006).

DOI: 10.1109/icpr.2006.697