Color Harmony for Image Indexing
Abstract
A predictive model for estimating the perceived harmony of ordinary multi-colored images is proposed and evaluated. The model is based on earlier research concerning two-color harmonies. Color regions of images are extracted using mean shift segmentation. Global and local harmony scores are derived for two-color combinations included in different subsets of all segmented regions. Statistical measurements of the obtained harmony scores are used for predicting the perceived overall harmony. The model is validated in a psychophysical experiment, where human observers are judging images on a harmony scale. The findings show that humans do perceive harmony in multi-colored images in similar ways, and that the proposed model results in useful predictions of harmony. The model can be applied in automatic labeling or classification of images.
Cite
Text
Solli and Lenz. "Color Harmony for Image Indexing." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457512Markdown
[Solli and Lenz. "Color Harmony for Image Indexing." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/solli2009iccvw-color/) doi:10.1109/ICCVW.2009.5457512BibTeX
@inproceedings{solli2009iccvw-color,
title = {{Color Harmony for Image Indexing}},
author = {Solli, Martin and Lenz, Reiner},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2009},
pages = {1885-1892},
doi = {10.1109/ICCVW.2009.5457512},
url = {https://mlanthology.org/iccvw/2009/solli2009iccvw-color/}
}