On-line graphics recognition

Xiangyu Jin; Wenyin Liu; Jianyong Sun; Zhengxing Sun

doi:10.1109/PCCGA.2002.1167869

On-line graphics recognition

Xiangyu Jin
, Wenyin Liu
, Jianyong Sun
, Zhengxing Sun

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

18 Citations (Scopus)

Abstract

A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divided the on-line graphics recognition process into four stages: preprocessing, shape classification, shape fitting, and regularization. The attraction force model is proposed to combine progressively the vertices on the input sketchy stroke and reduce the total number of vertices before the type of shape can be determined After that, the shape is fitted and gradually rectified to a regular one, thus the regularized shape fits the user-intended one precisely. Experimental results show that this algorithm can rapidly yield good recognition precision (averagely above 90%) and a fine regularization effect. Consequently, it is especially suitable for weak computation environments such as PDAs, which solely depend on a pen-based user interface. © 2002 IEEE.

Original language	English
Title of host publication	Proceedings - 10th Pacific Conference on Computer Graphics and Applications, PG 2002
Publisher	IEEE Computer Society
Pages	256-264
Volume	2002-January
ISBN (Print)	0769517846
DOIs	https://doi.org/10.1109/PCCGA.2002.1167869
Publication status	Published - 2002
Event	9th Pacific Conference on Computer Graphics and Applications, PG 2001 - Beijing, China Duration: 9 Oct 2002 → 11 Oct 2002

Publication series

Name	Proceedings - Pacific Conference on Computer Graphics and Applications
Volume	2002-January
ISSN (Print)	1550-4085

Conference

Conference	9th Pacific Conference on Computer Graphics and Applications, PG 2001
Place	China
City	Beijing
Period	9/10/02 → 11/10/02

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Research Keywords

Classification algorithms
Computer graphics
Computer science
Decision trees
Filters
Image segmentation
Personal digital assistants
Shape
Software algorithms
Sun

Access Output

10.1109/PCCGA.2002.1167869

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Cite this

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title = "On-line graphics recognition",

abstract = "A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divided the on-line graphics recognition process into four stages: preprocessing, shape classification, shape fitting, and regularization. The attraction force model is proposed to combine progressively the vertices on the input sketchy stroke and reduce the total number of vertices before the type of shape can be determined After that, the shape is fitted and gradually rectified to a regular one, thus the regularized shape fits the user-intended one precisely. Experimental results show that this algorithm can rapidly yield good recognition precision (averagely above 90\%) and a fine regularization effect. Consequently, it is especially suitable for weak computation environments such as PDAs, which solely depend on a pen-based user interface. {\textcopyright} 2002 IEEE.",

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Jin, X, Liu, W, Sun, J & Sun, Z 2002, On-line graphics recognition. in Proceedings - 10th Pacific Conference on Computer Graphics and Applications, PG 2002. vol. 2002-January, Proceedings - Pacific Conference on Computer Graphics and Applications, vol. 2002-January, IEEE Computer Society, pp. 256-264, 9th Pacific Conference on Computer Graphics and Applications, PG 2001, Beijing, China, 9/10/02. https://doi.org/10.1109/PCCGA.2002.1167869

On-line graphics recognition. / Jin, Xiangyu; Liu, Wenyin; Sun, Jianyong et al.
Proceedings - 10th Pacific Conference on Computer Graphics and Applications, PG 2002. Vol. 2002-January IEEE Computer Society, 2002. p. 256-264 (Proceedings - Pacific Conference on Computer Graphics and Applications; Vol. 2002-January).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - Liu, Wenyin

AU - Sun, Jianyong

AU - Sun, Zhengxing

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

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N2 - A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divided the on-line graphics recognition process into four stages: preprocessing, shape classification, shape fitting, and regularization. The attraction force model is proposed to combine progressively the vertices on the input sketchy stroke and reduce the total number of vertices before the type of shape can be determined After that, the shape is fitted and gradually rectified to a regular one, thus the regularized shape fits the user-intended one precisely. Experimental results show that this algorithm can rapidly yield good recognition precision (averagely above 90%) and a fine regularization effect. Consequently, it is especially suitable for weak computation environments such as PDAs, which solely depend on a pen-based user interface. © 2002 IEEE.

AB - A novel and fast shape classification and regularization algorithm for on-line sketchy graphics recognition is proposed. We divided the on-line graphics recognition process into four stages: preprocessing, shape classification, shape fitting, and regularization. The attraction force model is proposed to combine progressively the vertices on the input sketchy stroke and reduce the total number of vertices before the type of shape can be determined After that, the shape is fitted and gradually rectified to a regular one, thus the regularized shape fits the user-intended one precisely. Experimental results show that this algorithm can rapidly yield good recognition precision (averagely above 90%) and a fine regularization effect. Consequently, it is especially suitable for weak computation environments such as PDAs, which solely depend on a pen-based user interface. © 2002 IEEE.

KW - Classification algorithms

KW - Computer graphics

KW - Computer science

KW - Decision trees

KW - Filters

KW - Image segmentation

KW - Personal digital assistants

KW - Shape

KW - Software algorithms

KW - Sun

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SN - 0769517846

VL - 2002-January

T3 - Proceedings - Pacific Conference on Computer Graphics and Applications

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BT - Proceedings - 10th Pacific Conference on Computer Graphics and Applications, PG 2002

PB - IEEE Computer Society

T2 - 9th Pacific Conference on Computer Graphics and Applications, PG 2001

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ER -

On-line graphics recognition

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Research Keywords

Access Output

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