关键词: 图像检索, 高斯混合模型, KL散度, 移地距离, 颜色空间分布

Abstract:

To improve the computation efficiency and effectiveness of the similarity measure method between two Gaussian Mixture Models (GMM), a new measure method was proposed by means of integrating symmetrized Kullback-Leibler Divergence (KLD) and earth mover's distance. At first, the KL divergence between Gaussian components of the two GMMs to be compared was computed and symmetrized for constructing the earth distance matrix. Then, the earth mover's distance between the two GMMs was computed using linear programming and it was used for GMM similarity measure. The new measure method was tested in colorful image retrieval. The experimental results show that the proposed method is more effective and efficient than the traditional measure methods.

Key words: image retrieval, Gaussian mixture model, KL divergence, earth mover’s distance, color spatial distribution