Writer Adaptation for Online Handwriting Recognition System Using Virtual Examples

For an online handwriting recognition system equipped with a writer-independent classifier to progressively improve the recognition performance for a specific writer with an increase in his/her handwriting inputs, the following method is proposed: (1) For a handwriting pattern that causes a recognition error, a two-class classifier of the corresponding class is (re)constructed as a part of a writer-dependent classifier, separately from the writerindependent one, where artificially generated examples are used to compensate for lack of training examples. (2) In the recognition stage, the writerindependent classifier is applied first, and then the constructed writer-dependent classifier is used only in cases in which a result obtained by the writerindependent classifier possesses lower reliability. We examine the effectiveness of the proposed method using 6,000 Japanese Hiragana characters written by 3 users. As a result, an average recognition rate of 98.07% was obtained by the exclusiv...

• Type: Conference
• Year: 2009
• Where: ICDAR
• Authors: Hidetoshi Miyao, Minoru Maruyama
• Keywords: Document Analysis, ICDAR 2009, Writer-dependent Classifier, Writer-independent Classifier, Writerindependent Classifier