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  1. 紀要類
  2. 情報研究
  3. 第44号

A Method for Detecting Boundary Edges Based on a Local Image-Feature Integration Method

https://bunkyo.repo.nii.ac.jp/records/3190
https://bunkyo.repo.nii.ac.jp/records/3190
069f24d9-4494-4845-bf58-1e6d46fd41b0
名前 / ファイル ライセンス アクション
BKSJ440003.pdf BKSJ440003.pdf (905.6 kB)
Item type 紀要論文 / Departmental Bulletin Paper(1)
公開日 2011-02-16
タイトル
タイトル A Method for Detecting Boundary Edges Based on a Local Image-Feature Integration Method
言語
言語 eng
キーワード
主題 Region boundary, Boundary detection, Contour detection, Edge detection, Edge saliency, Canny
資源タイプ
資源タイプ departmental bulletin paper
著者 Shimodaira, Hisashi

× Shimodaira, Hisashi

Shimodaira, Hisashi

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所属機関
値 文教大学情報学部
内容記述
内容記述タイプ Abstract
内容記述 In an image, boundaries between regions represent the shapes of objects in the scene. Finding the boundaries is a problem of fundamental importance in the area of computer vision such as object recognition whose accuracy depends on the quality of the estimates of the boundaries. This paper proposes a method for detecting boundary edges based on a local image-feature integration method using a modified Canny edge detector. In the proposed method, first by edge saliency indices , salient edge are selected from the output of the modified Canny edge detector. Next , by boundary likelihood indices, edges with high boundary likelihood are selected from the salient edges. The major features of our method are as follows ; the algorithm is simple and easy to implement ; the computational complexity is not so high ; the paramater values once tuned for several images can be used in common for other images ; the good thresholds for selecting boundary edges are automatically computed. We have performed experiments on various natural images. The results have shown that our method works effectively and can produce relatively good estimates of boundary edges and its performance is robust.
書誌情報 情報研究
en : Information and Communication Studies

巻 44, p. 15-40, 発行日 2011-01-01
出版者
出版者 文教大学
ISSN
収録物識別子タイプ ISSN
収録物識別子 03893367
著者版フラグ
出版タイプ VoR
本文言語
値 英語
ID
値 BKSJ440003
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