Unsupervised manifold learning by correlation graph and strongly connected components for image retrieval

Daniel Carlos Guimaraes Pedronette, Ricardo da S. Torres
2014 2014 IEEE International Conference on Image Processing (ICIP)  
This paper presents a novel manifold learning approach that takes into account the intrinsic dataset geometry. The dataset structure is modeled in terms of a Correlation Graph and analyzed using Strongly Connected Components (SCCs). The proposed manifold learning approach defines a more effective distance among images, used to improve the effectiveness of image retrieval systems. Several experiments were conducted for different image retrieval tasks involving shape, color, and texture
more » ... d texture descriptors. The proposed approach yields better results in terms of effectiveness than various methods recently proposed in the literature.
doi:10.1109/icip.2014.7025379 dblp:conf/icip/PedronetteT14 fatcat:n2qg3cyxtzghznvhljllup43ai