Abstract
We propose a novel retrieval method for fractal coded images in the compressed data domain. A fractal code is a contractive affine mapping that represents a similarity relation between two regions in an image. A fractal coded image consists of a set of these contractive mappings. Each mapping can be approximately represented by a vector spanning two regions. Therefore, a fractal coded image can be approximated as a set of vectors. By introducing a new similarity measure that reflects the difference of distribution and cardinality between two vector sets, a novel retrieval method for fractal coded images is realized. We also propose a new efficient retrieval method using upper bounds of the similarity measure. The effectiveness of the proposed method is also illustrated by various experiments.
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Yokoyama, T., Watanabe, T., Koga, H. (2005). Similarity-Based Retrieval Method for Fractal Coded Images in the Compressed Data Domain. In: Leow, WK., Lew, M.S., Chua, TS., Ma, WY., Chaisorn, L., Bakker, E.M. (eds) Image and Video Retrieval. CIVR 2005. Lecture Notes in Computer Science, vol 3568. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526346_42
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DOI: https://doi.org/10.1007/11526346_42
Publisher Name: Springer, Berlin, Heidelberg
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