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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
Citation:
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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