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Recognition of Farsi Handwritten Numbers Using the Fuzzy Method
Mansoreh Sharizfadeh, Shahpour Alirezaee
Pages - 623 - 634     |    Revised - 01-11-2011     |    Published - 15-12-2011
Published in International Journal of Image Processing (IJIP)
Volume - 5   Issue - 5    |    Publication Date - November / December 2011  Table of Contents
MORE INFORMATION
References   |   Abstracting & Indexing
KEYWORDS
Character Recognition, Fuzzy, Geometric Feature
ABSTRACT
There are wide varieties of handwritten characters which differ not only from person to person but also from the state of mood of the same person. Nevertheless humans are trained to extract the specific features characterizing a symbol. This paper aims to introduce fuzziness in the definition of the proposed pattern features, which provides the enhancement to the handwritten character information to be stored. Some novel shape features in fuzzy linguistic domain are proposed. The experimental results indicate 95 % accuracy on recognition of Farsi numbers over the selected database.
ABSTRACTING & INDEXING
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REFERENCES
A.Malaviya, L. Peters “Fuzzy Feature Description of Handwriting Patterns” German National Research Center for Information Technology Schloß Birlinghoven, 53754, St. Augustin Pattern Recognition Volume 30, Issue 10, 1997.
C.Liu, S.Jaeger,M.Nakagawa “Online Recognition of Chinese Characters:The State-of-the-Art” IEEE transaction onpattern analysis and machine intelligence,VOL. 26, NO. 2, 2004.
Cheung K., Yeung D., “Bidirectional Deformable Matching with Application toHandwritten Character Extraction”, IEEE Transactions on Pattern Analysis and MachineIntelligence, Vol. 24, No. 8, August 2002.
Kim G., Kim S., “Feature Selection Using Genetic Algorithms for Handwritten CharacterRecognition“, Proceeding of the Sixth ACM SIGKDD International Conference onKnowledge Discovery and Data Mining, 2002.
Koerich A.L., Leydier Y., “A Hybrid Large Vocabulary Word Recognition System using Neural Networks with Hidden Markov Models”, IWFHR 2002.
Lee S., Kim Y., “A new type of recurrent neural network for handwritten characterrecognition”, Third International Conference on Document Analysis and Recognition (Volume 1), 1995.
Malaviya A. and Peters L., "Extracting meaningful handwriting features with fuzzyaggregation method", 3rd International conference on document analysis and recognition,ICDAR`95, pp. 841-844, Montreal, Canada, 1995.
R.Ranawana, V.Palade, G.Bandana “An Efficient Fuzzy Method for Handwritten Character Recognition” LNAI 3214, pp. 698–707, 2004.
MANUSCRIPT AUTHORS
Mansoreh Sharizfadeh
- Iran
Dr. Shahpour Alirezaee
- Iran
sh_alirezaee@yahoo.com


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