Abstract
In this paper, a new content-based image retrieval approach is proposed based on high-dimensional information theory. The proposed approach overcomes the disadvantages of the current content-based image retrieval algorithms that suffer from the semantic gap. First, we present a new multidimensional information space’s vector angle cosine algorithm of high-dimensional geometry, then, we provide a detailed description of our images retrieval method including proposal of an overlapping image block method and definition of a similarity degree between images on the non-dimensional information subspaces. Finally, experimental results show the higher retrieval efficiency of the proposed algorithm.
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Cao, W., Liu, N., Kong, Q. et al. Content-based image retrieval using high-dimensional information geometry. Sci. China Inf. Sci. 57, 1–11 (2014). https://doi.org/10.1007/s11432-014-5086-8
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DOI: https://doi.org/10.1007/s11432-014-5086-8