Abstract
Visual similarity evaluation plays an important role in intelligent graphics system. A basic problem of it is how to extract the content information of an image and how to describe the information with an intermediate representation, namely, image representation, because the image representation has great influence on the efficiency and performance of the similarity evaluation. In this paper, we focus on the domain of symbolic image recognition and introduce the Directional Division Tree representation, which is the image representation used in our algorithm. The conducted experiment shows that similarity evaluation algorithm based on this representation can yield satisfactory efficiency and performance.
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Huang, G., Zhang, W., Wenyin, L. (2008). A Discriminative Representation for Symbolic Image Similarity Evaluation. In: Liu, W., Lladós, J., Ogier, JM. (eds) Graphics Recognition. Recent Advances and New Opportunities. GREC 2007. Lecture Notes in Computer Science, vol 5046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88188-9_8
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DOI: https://doi.org/10.1007/978-3-540-88188-9_8
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