“Silhouette Image Recognition with Weighted Minimum Common Supergraph”

研究成果: Article査読

抄録

It is desired to recognize objects in images correctly. Recognition using structural feature has been studied. A single structure extracted by the medial axis transform from a digital silhouette image is not always an essential feature as a prototype that represents silhouettes in a category, because of noise and distortion. In this paper, we propose a method for recognizing silhouette images by obtaining an essential structure from the images of a category. The essential structure is defined as a weighted minimum common supergraph of graphs which are extracted from silhouette images. To show the validly of the proposed method, experiments are carried out for categorizing silhouette images.

本文言語English
ページ(範囲)640-647
ページ数8
ジャーナルJournal of the Institute of Image Electronics Engineers of Japan
38
5
DOI
出版ステータスPublished - 2009 1

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Electrical and Electronic Engineering

フィンガープリント 「“Silhouette Image Recognition with Weighted Minimum Common Supergraph”」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル