群化要因に基づくドロネー分割を用いた視覚的連続曲線の認識

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2011/09/01

タイトル(英語): Curves Detection Using Delaunay Triangulation Based on Perceptual Grouping Factors

著者名: 高城　貴光（岐阜大学工学部応用情報学科），斉藤　文彦（岐阜大学工学部応用情報学科）

著者名(英語): Takamitsu Takagi (Department of Information Science, Faculty of Engineering, Gifu University), Fumihiko Saitoh (Department of Information Science, Faculty of Engineering, Gifu University)

キーワード: 群化要因，ドロネー三角形分割，曲線認識　　perceptual grouping factors，Delaunay triangulation，curves detection

要約(英語): In this paper, we propose a method to detect perceptual continuous curves in a binary image including discontinuous curves and noises based on perceptual grouping factors. Firstly, making a Delaunay diagram from a binary image, adjacency relation is obtained. Secondly, the method selects a Delaunay edge as the starting line and connects a certain number of points. When the points have maximum evaluation value based on perceptual grouping factors, they construct an appropriate partial curve. Evaluation value of an appropriate partial curve is added to Delaunay edges selected by it. Finally, Delaunay edges that have high evaluation value are extracted. Experimental results show that proposed method has yielded results that are similar to visual curves and better than conventional methods.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.131 No.9 （2011） 特集：医療・ヘルスケアにおける工学技術の新展開

本誌掲載ページ: 1616-1624 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/131/9/131_9_1616/_article/-char/ja/