Abstract
This paper aims at presenting novel approach for curve matching and character recognition such as printed writing, handwriting, signatures, etc. based on B-Spline curve. The advantages of the B-Spline that are continuous curve representation and affine invariant, and the robustness. The recognition process is composed of two main steps: sample training and recognition. The computer must be trained with data from bitmap image file. The next step is pre-processing input data from the binary image and finding its skeleton. The reconstruction of a B-Spline curve representing the sample character is applied to find out the control points. Then the sample B-spline curve of each character is stored in a database. For the test character, it has the same process with the sample character. The matching is done by computing the Euclidean distance between the control points of test curve with those of all sample characters to recognize the character. The experimental results show the performance of the proposed algorithm.
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© 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Nguyen-Tan, K., Nguyen-Hoang, N. (2013). Handwriting Recognition Using B-Spline Curve. In: Vinh, P.C., Hung, N.M., Tung, N.T., Suzuki, J. (eds) Context-Aware Systems and Applications. ICCASA 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36642-0_33
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DOI: https://doi.org/10.1007/978-3-642-36642-0_33
Publisher Name: Springer, Berlin, Heidelberg
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