Authors:
Xi-Wen Zhang
;
Hao Bai
and
Yong-Gang Fu
Affiliation:
Beijing Language and Culture University, China
Keyword(s):
Digital Ink Text, Segmentation, Visualization, Adaptive, Context.
Related
Ontology
Subjects/Areas/Topics:
Biometrics and Pattern Recognition
;
Human-Machine Interface
;
Multimedia
;
Multimedia Signal Processing
;
Multimedia Systems and Applications
;
Semantic Analysis of Multimedia Data
;
Telecommunications
Abstract:
Digital ink texts in Chinese can neither be converted into users’ desired layouts nor be recognized until they are segmented correctly. There are many errors in automatically segmented results because the texts are free forms and mixed with other languages, as well as their Chinese characters have small gaps and complex structures. Paragraphs, text lines, and characters (recognizable language symbols) may be wrongly extracted. It is a prerequisite to visualize segmented results for further correcting wrong extracted objects using human-computer interaction. Thus, an adaptive approach based on context is proposed to visualize segmented digital ink texts in Chinese. Each extracted object is adaptively visualized by shape and colour labels according to relations between it and its neighbours. Confidences of extracted objects are also visualized with bounding shapes with different line widths. Each object’s contexts are constructed from it and other objects invoked by it, where an optimu
m visualization is identified. We have conducted experiments using real-life segmented digital ink texts in Chinese and compared the proposed approach with others. Experimental results demonstrate that the proposed approach is feasible, flexible, and effective.
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