The spatiogram features have been widely used in computer vision. In this paper, in order to improve the
performance of image retrieval method based on spatiogram features, we propose a new method to measure the
spatiogram similarity in the framework of extended Gaussian Lie group model. In our method, the spatiogram features
are extracted in the HSV space. The similarity between images described by spatiogram features depends on the
distances between Gaussian probability density functions which can be calculated using Lie group theory. Based on the
framework of the extended Gaussian matrix Lie group, the contribution of the covariance matrix and the mean vector is
adjusted automatically, which ensures both the covariance matrix and the mean vector will not be ignored when
calculating the image similarity in the process of retrieval. We test our algorithm on the WANG Image Database.
Experiments show that the proposed method has a better performance than the method based on the traditional Gaussian
Lie group.
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