This thesis describes a computational approach for analyzing the color aesthetics
of images from the perspective of color theory. Our work has been informed by the
works of Johannes Itten, one of the most influential theorists of color aesthetics.
To the best of our knowledge, developing computational models that are based on
Itten's theories is our unique contribution to Computer Vision. We focus on three
aspects of color usage in visual art, namely modulation, contrast of hue and cold-warm
contrast. For modulation, we introduce the color palette, a novel 3D visualization of
the chromatic information of an image in the HSL space and propose a set of simple
descriptors for evaluating color modulation. For contrast of hue, we assess the spatial
color composition of the homogeneous regions. For cold-warm contrast, we assess
the spatial color composition of the homogeneous regions and the hue adjacencies.
Further, we assess the relative warmth of the homogeneous regions and adjacent hues.
We also propose a visualization, namely a 3D histogram to visualize the patterns of the
contrasts in an artist's paintings. We validate our methods by comparing our results
with Itten's descriptions and comments. We hope that this computational approach
improves the color-based features used in the aesthetic classification of images. / Graduate / 0984
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/5625 |
| Date | 28 August 2014 |
| Creators | Agahchen, Anissa |
| Contributors | Branzan Albu, Alexandra |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
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