The traditional K-means algorithm is regarded that the attributes of swatches have the same effect on the clustering analysis. Based on AHP and CRITIC, comprehensive weighting of K-means clustering algorithm is proposed to solve the problem in this paper. First, each of attribute weight is calculated by CV-K-means method, thus judgment matrix is determined by comparing the two.Then, according to the analytic hierarchy process subjective weights of attributes is determined. And using the CRITIC method the objective weight of each attribute is determined, difference coefficient method is used to determine coefficient of combination. The experimental results show that the algorithm accuracy is higher than the traditional K-means algorithm.