Recent Trends and Tools for Feature Extraction in OCR Technology
Om Prakash Sharma1, M. K. Ghose2, Krishna Bikram Shah3, Benoy Kumar Thakur4

1Om Prakash Sharma, Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Majitar, Sikkim, India.
2Dr. M. K. Ghose, Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Majitar, Sikkim, India.
3Krishna Bikram Shah, Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, Majitar, Sikkim, India.
4Benoy Kumar Thakur, Department of Computer Science and Engineering, Rockvale Management College, Kalimpong, West Bengal, India.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 120-123 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1158112612/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper presents a recent trends and tools used for feature extraction that helps in efficient classification of the handwritten alphabets. Numerous models of feature extraction have been defined by different researchers in their respective dissertation. It is found that the use of Euler Number in addition to zoning increases the speed and the accuracy of the classifier as it reduces the search space by dividing the character set into three groups.
Keywords: Handwritten Character Recognition, Feature Extraction, Zoning, Euler Number, Classification.