Segmentation of On-line Handwritten Japanese Characters of Arbitrary Line Direction Using SVM(Internationa Session 6)

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概要

• 論文の詳細を見る

• 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.

• 一般社団法人電子情報通信学会の論文
• 2007-10-18

著者

• Nakagawa Masaki

  Tokyo Univ. Agriculture And Technol. Tokyo Jpn

• Zhu Bilan

  Tokyo Univ. Agriculture And Technol. Tokyo Jpn

• Zhu Bilan

  Tokyo University Of Agriculture And Technology

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• An Exam Scoring Application Running on Paper Architecture(Character and document processing)
• Segmentation of On-line Handwritten Japanese Characters of Arbitrary Line Direction Using SVM(Internationa Session 6)

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