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<p>We propose a new pattern representation scheme based on data compression, or PRDC, for media data analysis. PRDC is composed of two parts, an encoder that translates input data into a text and a set of text compressors to generate a compression ratio vector (CV). The CV is used as a feature of the input data. By preparing a set of media-specific encoders, PRDC becomes widely applicable. Analysis tasks, both categorization (class formation) and recognition (classification), can be realized using CVs. After a mathematical discussion on the realizability of PRDC, the wide applicability of this scheme is demonstrated through automatic categorization and/or recognition of music, voice, genome, handwritten sketches, and color images.</p>
Multimedia, pattern, analysis, categorization, recognition, feature space, compression ratio, generality, VQ

T. Watanabe, K. Sugawara and H. Sugihara, "A New Pattern Representation Scheme Using Data Compression," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 24, no. , pp. 579-590, 2002.
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