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A New Pattern Representation Scheme Using Data Compression
May 2002 (vol. 24 no. 5)
pp. 579-590

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.

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Index Terms:
Multimedia, pattern, analysis, categorization, recognition, feature space, compression ratio, generality, VQ
T. Watanabe, K. Sugawara, H. Sugihara, "A New Pattern Representation Scheme Using Data Compression," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 579-590, May 2002, doi:10.1109/34.1000234
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