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  • 标题:ファジィハフ変換による関数回帰
  • 本地全文:下载
  • 作者:岡田 正之 ; 半田 美恵 ; 松永 浩之
  • 期刊名称:映像情報メディア学会誌
  • 印刷版ISSN:1342-6907
  • 电子版ISSN:1881-6908
  • 出版年度:1997
  • 卷号:51
  • 期号:11
  • 页码:1899-1905
  • DOI:10.3169/itej.51.1899
  • 出版社:The Institute of Image Information and Television Engineers
  • 摘要:Function regression can be viewed as template matching in an augmented space spanned by independent variables and function values. This formulation of function regression enables us to reject out-lier data and to preserve discontinuities in functions. In this paper, such a function regression method based on fuzzy Hough transforms is presented. The implementation of this approach by using neural networks is illustrated, and a supervised learning algorithm based on function interpolation of sparse data is proposed. The present method is used in image smoothing, segmentation by clustering of image pixels, and is also used in random dot stereo vision including transparent patterns.
  • 关键词:関数回帰;ファジイハフ変換;平滑化;領域分割;ステレオ視覚
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