Detail publikace

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

Originální název

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

Anglický název

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

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

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",
  doi="10.1109/TSP.2015.7296366",
  howpublished="online",
  year="2015",
  month="july",
  pages="756--759",
  type="conference paper"
}