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Handwritten Recognition using Slope and Curvature Functions

Mehdi Yaghoubi, Soheila Karbasi Published in Pattern Recognition

International Journal of Applied Information Systems
Year of Publication: 2012
© 2012 by IJAIS Journal
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  1. Mehdi Yaghoubi and Soheila Karbasi. Article: Handwritten Recognition using Slope and Curvature Functions. International Journal of Applied Information Systems 4(8):17-20, December 2012. BibTeX

    	author = "Mehdi Yaghoubi and Soheila Karbasi",
    	title = "Article: Handwritten Recognition using Slope and Curvature Functions",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 4,
    	number = 8,
    	pages = "17-20",
    	month = "December",
    	note = "Published by Foundation of Computer Science, New York, USA"


Letter recognition and handwritten processing is one of the major and open problems in Artificial Intelligent (AI) domain. This study introduces a method based on statistical and geometrical techniques to recognize handwritten digits and letters. These techniques use the fuzzy logic to create the vector curves. Inputs are online digits or letters and outputs are two arrays of slope and curvature values. The slope and curvature values of training data are stored in a database and used in comparison phase. The test results show that 96. 98% of inputs are correctly recognized.


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Vector curve, Slope function, Curvature function