According to the problem of color recognition of
clothes for image searching on web, a kind of clustering main
color detection with one step of k-means and one step of mean
shift is adopted and the color of clothes can be detected
accurately. It uses the k-means to extract the background and
foreground of a picture, which contains the information of a
person dressed up with a color cloth in a complex background.
The first step aims to recognize the position of the cloth content
and lows the influence of the background. After the first step of
k-means, we reconstruct the image as the clustering data for the
second step of mean shift. The recognition effect achieves above
85% by calculating the distance of the clustering center of our
color model of pixel, comparing to the database with the
accurately color map of our clothes’ images. The experiment of
our approach shows that the two-steps k-means and mean shift of
color recognition is improved. We developed a color recognition
system of clothes for the image searching using that approach
and the recognition performance is optimized.