2014 IEEE Winter Conference on Applications of Computer Vision (WACV) (2014)
Steamboat Springs, CO, USA
March 24, 2014 to March 26, 2014
Yin Cui , Department of Electrical Engineering, Columbia University, USA
Yongzhou Xiang , Department of Electrical Engineering, Columbia University, USA
Kun Rong , Department of Electrical Engineering, Columbia University, USA
Rogerio Feris , IBM T. J. Watson Research Center, USA
Liangliang Cao , IBM T. J. Watson Research Center, USA
We propose a spatial-color layout feature specially designed for galaxy images. Inspired by findings on galaxy formation and evolution from Astronomy, the proposed feature captures both global and local morphological information of galaxies. In addition, our feature is scale and rotation invariant. By developing a hashing-based approach with the proposed feature, we implemented an efficient galaxy image retrieval system on a dataset with more than 280 thousand galaxy images from the Sloan Digital Sky Survey project. Given a query image, the proposed system can rank-order all galaxies from the dataset according to relevance in only 35 milliseconds on a single PC. To the best of our knowledge, this is one of the first works on galaxy-specific feature design and large-scale galaxy image retrieval. We evaluated the performance of the proposed feature and the galaxy image retrieval system using web user annotations, showing that the proposed feature outperforms other classic features, including HOG, Gist, LBP, and Color-histograms. The success of our retrieval system demonstrates the advantages of leveraging computer vision techniques in Astronomy problems.
Spirals, Feature extraction, Image color analysis, Shape, Layout, Image retrieval, Kernel
Yin Cui, Yongzhou Xiang, Kun Rong, R. Feris and L. Cao, "A spatial-color layout feature for representing galaxy images," 2014 IEEE Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, CO, USA, 2014, pp. 213-219.