Segmentation of On-line Handwritten Japanese Characters of Arbitrary Line Direction Using SVM
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This paper describes a method of producing segmentation point candidates for on-line handwritten Japanese text by a support vector machine (SVM) to improve text recognition. This method extracts multi-dimensional features from on-line strokes of handwritten text and applies the SVM to the extracted features to produces segmentation point candidates. This paper also shows the details of generating segmentation point candidates in order to achieve high discrimination rate by finding the optimal combination of the segmentation threshold and the concatenation threshold. We compare the method for segmentation by the SVM with that by a neural network (NN) and show the result that the method by the SVM bring about a better segmentation rate and character recognition rate.
- IEICE technical report
IEICE technical report 107(281), 135-140, 2007-10-18
The Institute of Electronics, Information and Communication Engineers