Research Article
Handwriting Recognition Using B-Spline Curve
@INPROCEEDINGS{10.1007/978-3-642-36642-0_33, author={Khoi Nguyen-Tan and Nguyen Nguyen-Hoang}, title={Handwriting Recognition Using B-Spline Curve}, proceedings={Context-Aware Systems and Applications. First International Conference, ICCASA 2012, Ho Chi Minh City, Vietnam, November 26-27, 2012, Revised Selected Papers}, proceedings_a={ICCASA}, year={2013}, month={2}, keywords={B-Spline curve matching curve handwriting Optical character recognition reconstruction}, doi={10.1007/978-3-642-36642-0_33} }- Khoi Nguyen-Tan
Nguyen Nguyen-Hoang
Year: 2013
Handwriting Recognition Using B-Spline Curve
ICCASA
Springer
DOI: 10.1007/978-3-642-36642-0_33
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.
