Color distribution matching using a weighted subspace descriptor

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

This paper presents a low-level color descriptor which describes the color distribution of a color image as a weighted subspace in the color space, namely eigenvectors and eigenvalues of the distribution. Thanks to low-dimensionality of color space, the proposed descriptor can provide compact description and fast computation. Furthermore, specialized for color distribution matching, it is more efficient than mutual subspace method (MSM). Experiments on medicine package recognition validate that the proposed descriptor outperforms MSM and MPEG-7 low-level color descriptors in terms of description size, computational cost and recognition rate.

元の言語English
ホスト出版物のタイトルICIP 2011
ホスト出版物のサブタイトル2011 18th IEEE International Conference on Image Processing
ページ1697-1700
ページ数4
DOI
出版物ステータスPublished - 2011 12 1
イベント2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
継続期間: 2011 9 112011 9 14

出版物シリーズ

名前Proceedings - International Conference on Image Processing, ICIP
ISSN(印刷物)1522-4880

Conference

Conference2011 18th IEEE International Conference on Image Processing, ICIP 2011
Belgium
Brussels
期間11/9/1111/9/14

    フィンガープリント

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

これを引用

Sugimoto, K., & Kamata, S. I. (2011). Color distribution matching using a weighted subspace descriptor. : ICIP 2011: 2011 18th IEEE International Conference on Image Processing (pp. 1697-1700). [6115783] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2011.6115783