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Video-based handwritten Chinese char...

Lin, Feng.

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Video-based handwritten Chinese character recognition.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Video-based handwritten Chinese character recognition./
Author:	Lin, Feng.
Description:	130 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3439.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3099302

Video-based handwritten Chinese character recognition.
Lin, Feng.

Video-based handwritten Chinese character recognition. - 130 p.

Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3439.

Thesis (Ph.D.)--Chinese University of Hong Kong (People's Republic of China), 2003.

In this thesis, we develop a novel Video-based handwritten character recognition (VCR) system focusing on the recognition of Chinese handwritten characters. The main problem of VCR system is how to effectively extract stroke dynamic information from video data for character recognition. We design a stroke extraction algorithm that utilizes the combination of stroke static information analysis and dynamic information analysis. Static information analysis relies on the static/spatial information of character image to extract the character stroke. Based on the result of static information analysis, dynamic information analysis is then performed to extract all the dynamic/temporal information of character strokes. The recovered character information is analogous to that of on-line systems, so a conventional on-line method can be utilized for the character recognition.

Video-based handwritten Chinese character recognition.
LDR:02109nmm 2200181 4500 001 1853590
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008 130614s2003 eng d
035 $a (UnM)AAI3099302
035 $a AAI3099302
040 $a UnM $c UnM
100 1 $a Lin, Feng. $3 1941451
245 1 0 $a Video-based handwritten Chinese character recognition.
300 $a 130 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-07, Section: B, page: 3439.
500 $a Adviser: Xiaoou Sean Tang.
502 $a Thesis (Ph.D.)--Chinese University of Hong Kong (People's Republic of China), 2003.
520 $a In this thesis, we develop a novel Video-based handwritten character recognition (VCR) system focusing on the recognition of Chinese handwritten characters. The main problem of VCR system is how to effectively extract stroke dynamic information from video data for character recognition. We design a stroke extraction algorithm that utilizes the combination of stroke static information analysis and dynamic information analysis. Static information analysis relies on the static/spatial information of character image to extract the character stroke. Based on the result of static information analysis, dynamic information analysis is then performed to extract all the dynamic/temporal information of character strokes. The recovered character information is analogous to that of on-line systems, so a conventional on-line method can be utilized for the character recognition.
520 $a To extract the character static information, we propose a novel off-line Chinese stroke extraction method. We investigate all the skeleton points that exist in a skeleton character image, and improve the feature point detection method based on Rutoviz's crossing number definition. Using a new bi-directional graph, we successfully connect Chinese character stroke segments. The algorithm can accurately extract the strokes from the thinned Chinese character images. Extensive experimental results on over eighteen thousand character strokes show our method can achieve over 99% accuracy
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3099302