Color Content Descriptors of Images by Vector Quantization
Jan Mihalik, Iveta Gladisova
DOI: 10.15598/aeee.v18i4.3799
Abstract
In the paper, we propose color content descriptors of images by vector quantization in RGB color space in order to obtain a much more accurate discrete representation of this space using our algorithm for optimization of vector quantizers compared to scalar ones. We introduce several modifications of these descriptors such as global, structural as well as of dominant color. We consider a different number of bins and evaluated the similarity of the color content of images using mean square error of color histograms of a reference image and a searched image. Then, the color content of the image with the minimum error was the most similar to the reference image. We also used a parameter of variance, if the color content of several searched images was very similar based on the mean quadratic error for the structural descriptor.