Content based image retrieval using extended Gaussian Lie group spatiogram similarity

Feng Cheng; Xiaqiong Yu; Zuxi Wang; Dehua Li

doi:10.1117/12.2030728

19 July 2013 Content based image retrieval using extended Gaussian Lie group spatiogram similarity

Feng Cheng, Xiaqiong Yu, Zuxi Wang, Dehua Li

Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 887812 (2013) https://doi.org/10.1117/12.2030728
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China

Abstract

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.

Citation Download Citation

Feng Cheng, Xiaqiong Yu, Zuxi Wang, and Dehua Li "Content based image retrieval using extended Gaussian Lie group spatiogram similarity", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 887812 (19 July 2013); https://doi.org/10.1117/12.2030728

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