A Line Smoothing Method of Hand-Drawn Strokes Using Adaptive Moving Average for Illustration Tracing Tasks

Hotaka KAWASE; Mikio SHINYA; Michio SHIRAISHI

doi:10.1587/transinf.E95.D.2704

A Line Smoothing Method of Hand-Drawn Strokes Using Adaptive Moving Average for Illustration Tracing Tasks

Hotaka KAWASE, Mikio SHINYA, Michio SHIRAISHI

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There are many web sites where net users can post and distribute their illustration images. A typical way to draw a digital illustration is first to draw rough lines on a paper and then to trace the lines on a graphics-tablet by hand. The input lines usually contain fluctuation due to hand-drawing, which limits the quality of illustration. Therefore, it is important to remove the fluctuation and to smooth the lines while maintaining sharp features such as corners. Although naive applications of moving average filters can smooth input lines, they may cause over-smoothing artifacts in which sharp features are lost by the filtering. This paper describes an improved line smoothing method using adaptive moving averages, which smoothes input lines while keeping high curvature points. The proposed method evaluates curvatures of input lines and adaptively controls the filter-size to reduce the over-smoothing artifacts. Experiments demonstrated advantages of the proposed method over the previous method in terms of achieving smoothing effect while still preserving sharp feature preservation.

Publication: IEICE TRANSACTIONS on Information Vol.E95-D No.11 pp.2704-2709

Publication Date: 2012/11/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1587/transinf.E95.D.2704

Type of Manuscript: PAPER

Category: Computer Graphics

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Hotaka KAWASE, Mikio SHINYA, Michio SHIRAISHI, "A Line Smoothing Method of Hand-Drawn Strokes Using Adaptive Moving Average for Illustration Tracing Tasks" in IEICE TRANSACTIONS on Information, vol. E95-D, no. 11, pp. 2704-2709, November 2012, doi: 10.1587/transinf.E95.D.2704.
Abstract: There are many web sites where net users can post and distribute their illustration images. A typical way to draw a digital illustration is first to draw rough lines on a paper and then to trace the lines on a graphics-tablet by hand. The input lines usually contain fluctuation due to hand-drawing, which limits the quality of illustration. Therefore, it is important to remove the fluctuation and to smooth the lines while maintaining sharp features such as corners. Although naive applications of moving average filters can smooth input lines, they may cause over-smoothing artifacts in which sharp features are lost by the filtering. This paper describes an improved line smoothing method using adaptive moving averages, which smoothes input lines while keeping high curvature points. The proposed method evaluates curvatures of input lines and adaptively controls the filter-size to reduce the over-smoothing artifacts. Experiments demonstrated advantages of the proposed method over the previous method in terms of achieving smoothing effect while still preserving sharp feature preservation.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.2704/_p

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@ARTICLE{e95-d_11_2704,
author={Hotaka KAWASE, Mikio SHINYA, Michio SHIRAISHI, },
journal={IEICE TRANSACTIONS on Information},
title={A Line Smoothing Method of Hand-Drawn Strokes Using Adaptive Moving Average for Illustration Tracing Tasks},
year={2012},
volume={E95-D},
number={11},
pages={2704-2709},
abstract={There are many web sites where net users can post and distribute their illustration images. A typical way to draw a digital illustration is first to draw rough lines on a paper and then to trace the lines on a graphics-tablet by hand. The input lines usually contain fluctuation due to hand-drawing, which limits the quality of illustration. Therefore, it is important to remove the fluctuation and to smooth the lines while maintaining sharp features such as corners. Although naive applications of moving average filters can smooth input lines, they may cause over-smoothing artifacts in which sharp features are lost by the filtering. This paper describes an improved line smoothing method using adaptive moving averages, which smoothes input lines while keeping high curvature points. The proposed method evaluates curvatures of input lines and adaptively controls the filter-size to reduce the over-smoothing artifacts. Experiments demonstrated advantages of the proposed method over the previous method in terms of achieving smoothing effect while still preserving sharp feature preservation.},
keywords={},
doi={10.1587/transinf.E95.D.2704},
ISSN={1745-1361},
month={November},}

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TY - JOUR
TI - A Line Smoothing Method of Hand-Drawn Strokes Using Adaptive Moving Average for Illustration Tracing Tasks
T2 - IEICE TRANSACTIONS on Information
SP - 2704
EP - 2709
AU - Hotaka KAWASE
AU - Mikio SHINYA
AU - Michio SHIRAISHI
PY - 2012
DO - 10.1587/transinf.E95.D.2704
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2012
AB - There are many web sites where net users can post and distribute their illustration images. A typical way to draw a digital illustration is first to draw rough lines on a paper and then to trace the lines on a graphics-tablet by hand. The input lines usually contain fluctuation due to hand-drawing, which limits the quality of illustration. Therefore, it is important to remove the fluctuation and to smooth the lines while maintaining sharp features such as corners. Although naive applications of moving average filters can smooth input lines, they may cause over-smoothing artifacts in which sharp features are lost by the filtering. This paper describes an improved line smoothing method using adaptive moving averages, which smoothes input lines while keeping high curvature points. The proposed method evaluates curvatures of input lines and adaptively controls the filter-size to reduce the over-smoothing artifacts. Experiments demonstrated advantages of the proposed method over the previous method in terms of achieving smoothing effect while still preserving sharp feature preservation.
ER -