Segmentation and reconstruction of on-line handwritten scripts

被引:25
作者
Li, XL
Parizeau, M [1 ]
Plamondon, R
机构
[1] Univ Laval, Dept Genie Elect & Genie Informat, Quebec City, PQ G1K 7P4, Canada
[2] Ecole Polytech, Dept Genie Elect & Genie Informat, Montreal, PQ H3C 3A7, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
delta log-normal model; static stroke; extrema of curvature; inflection points; landmark points; segmentation; reconstruction; data compression;
D O I
10.1016/S0031-3203(97)00086-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
On-line handwritten scripts consist of sequences of components that are pen tip traces from pen-down to pen-up positions. This paper presents a segmentation and reconstruction procedure which segments components of a script into sequences of static strokes, and then reconstructs the script From these sequences. The segmentation is based on the extrema of curvature and inflection points in individual components. The static strokes are derived from the delta log-normal model of handwriting generation and are used in component representation and reconstruction. The performance of the procedure is measured in terms of root-mean-square reconstruction error and data compression rate. (C) 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:675 / 684
页数:10
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