Publication detail

Color Image (Dis)Similarity Assessment and Grouping based on Dominant Colors

KARÁSEK, J. BURGET, R. UHER, V. MAŠEK, J. DUTTA, M.

Original Title

Color Image (Dis)Similarity Assessment and Grouping based on Dominant Colors

English Title

Color Image (Dis)Similarity Assessment and Grouping based on Dominant Colors

Type

conference paper

Language

en

Original Abstract

The computer vision connected to image understanding becomes more and more important in everyday life. This paper concerns the image (dis)similarity assessment and grouping. The main contribution of this paper is the method for image (dis)similarity assessment based on dominant colors. The experimental results showed better results than the Direct Pixel Similarity and Color Histograms and method proved to be capable of detecting images similar to the target image.

English abstract

The computer vision connected to image understanding becomes more and more important in everyday life. This paper concerns the image (dis)similarity assessment and grouping. The main contribution of this paper is the method for image (dis)similarity assessment based on dominant colors. The experimental results showed better results than the Direct Pixel Similarity and Color Histograms and method proved to be capable of detecting images similar to the target image.

Keywords

Categorization, Classification, Clustering, Computer Vision, Image Processing, Image Similarity Measure

RIV year

2014

Released

01.07.2014

Location

Berlin, Germany

ISBN

978-80-214-4983-1

Book

2014 37th International Conference on Telecommunications and Signal Processing (TSP)

Pages from

631

Pages to

634

Pages count

4

BibTex


@inproceedings{BUT107112,
  author="Jan {Karásek} and Radim {Burget} and Václav {Uher} and Jan {Mašek} and Malay Kishore {Dutta}",
  title="Color Image (Dis)Similarity Assessment and Grouping based on Dominant Colors",
  annote="The computer vision connected to image understanding becomes more and more important in everyday life. This paper concerns the image (dis)similarity assessment and grouping. The main contribution of this paper is the method for image (dis)similarity assessment based on dominant colors. The experimental results showed better results than the Direct Pixel Similarity and Color Histograms and method proved to be capable of detecting images similar to the target image.",
  booktitle="2014 37th International Conference on Telecommunications and Signal Processing (TSP)",
  chapter="107112",
  howpublished="online",
  year="2014",
  month="july",
  pages="631--634",
  type="conference paper"
}