Title :
Overlapped Handwriting Input on Mobile Phones
Author :
Zou, Yanming ; Liu, Yingfei ; Liu, Ying ; Wang, Kongqiao
Author_Institution :
Nokia Res. Center, BDA, Beijing, China
Abstract :
In this paper, we propose an overlapped handwriting input method on handheld devices, which allows users to write continuously without breaks on a single size-restricted writing area. 2 issues have been considered during the implementation of the overlapped input method: previous characters on the background may obstruct the clear viewing of current character and the messy overlapped handwriting is difficult to be segmented and recognized. In our method, a quick segmentation method based on an artificial neural network is used to tackle the first problem and a novel system is implemented to recognize the messy handwriting based on the output of an isolated character recognition engine and a language model. The recognition rate for Chinese characters is about 92.5% for a testing database containing GB2312 Chinese characters and other frequently used symbols. The positive feedbacks from testers have also confirmed the validity of the proposed method.
Keywords :
handwriting recognition; image segmentation; mobile computing; mobile handsets; natural language processing; neural nets; Chinese characters; artificial neural network; handheld devices; image segmentation method; mobile phones; overlapped handwriting input; Character recognition; Engines; Handheld computers; Handwriting recognition; Testing; Training; Writing; artificial neural network; language model; overlapped handwriting recognition;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2011.82