Journal of System Simulation
Abstract
Abstract: For color transfer between colorful images, we used K-means clustering to classify image pixels and we also proposed nearest region matching algorithm. This algorithm can avoid the problem that multiple regions matched to the same region, and it can get the best match results between the two images. Translate the color space from RGB to for the two images. Divide color image and luminance mapped shape image using K-means models into the same number of classes. Determine the relationship between regions of the two images using Euclidean distance and the nearest region matching algorithm. Complete color transfer from color image to the shape image. Experimental results show that the algorithm can achieve the color transfer better for colorful images.
Recommended Citation
Zhang, Ziying; Zhou, Mingquan; Shui, Wuyang; Wu, Zhongke; and Xia, Zheng
(2020)
"Color Transfer Based on K-means Clustering Algorithm and Region Matching,"
Journal of System Simulation: Vol. 27:
Iss.
10, Article 20.
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol27/iss10/20
First Page
2359
Revised Date
2015-07-24
DOI Link
https://doi.org/
Last Page
2364
CLC
TP391.4
Recommended Citation
Zhang Ziying, Zhou Mingquan, Shui Wuyang, Wu Zhongke, Zheng Xia. Color Transfer Based on K-means Clustering Algorithm and Region Matching[J]. Journal of System Simulation, 2015, 27(10): 2359-2364.
Included in
Artificial Intelligence and Robotics Commons, Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Science Commons