Extraction of Structure of Silhouette Images by Weighted Minimum Common Supergraph(Internationa Session 2)
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概要
- 論文の詳細を見る
It is desired to recognize objects which are distorted or rotated in images. Since it is difficult to recognize those objects by template matching in images, recognition using graph has been studied. A graph extracted by medial axis transform to a digital silhouette image is not always a graph which represents the essential structure that distincts silhouettes in a category, because of noise and distortion. Our aim in this paper is to extract the essential structure of silhouette. We propose a method to extract the structure by weighted minimum common supergraph. To show the validity of the proposed method, experiments are carried out for categorizing silhouette images using the extracted structure.
- 社団法人電子情報通信学会の論文
- 2007-10-18
著者
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Omachi Shinichiro
Graduate School Of Engineering Tohoku University
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Omachi Shinichiro
Tohoku Univ. Sendai‐shi Jpn
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Aso Hirotomo
Graduate School Of Engineering Tohoku University
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MIYAZAKI Tomo
Graduate school of Engineering, Tohoku University
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Miyazaki Tomo
Tohoku Univ.
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Miyazaki Tomo
Graduate School Of Engineering Tohoku University
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