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[Author] Kazumi ODAKA(2hit)

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  • A Portable Magnetic-Noise Free Visual Stimulator for MEG Measurements

    Kazumi ODAKA  Toshiaki IMADA  Takunori MASHIKO  Minoru HAYASHI  

     
    LETTER-Medical Electronics and Medical Information

      Vol:
    E79-D No:2
      Page(s):
    165-169

    This letter shows that a portable visual stimulator for MEG measurements can be realized using an optical fiber bundle and a CRT display system offering high brightness and high speed raster scanning, and that MEGs with neither magnetic contamination nor jitter can be measured by the stimulator.

  • Stroke-Number and Stroke-Order Free On-Line Kanji Character Recognition as One-to-One Stroke Correspondence Problem

    Toru WAKAHARA  Akira SUZUKI  Naoki NAKAJIMA  Sueharu MIYAHARA  Kazumi ODAKA  

     
    PAPER-Online Recognition

      Vol:
    E79-D No:5
      Page(s):
    529-534

    This paper describes an on-line Kanji character recognition method that solves the one-to-one stroke correspondence problem with both the stroke-number and stroke-order variations common in cursive Japanese handwriting. We propose two kinds of complementary algorithms: one dissolves excessive mapping and the other dissolves deficient mapping. Their joint use realizes stable optimal stroke correspondence without combinatorial explosion. Also, three kinds of inter-stroke distances are devised to deal with stroke concatenation or splitting and heavy shape distortion. These new ideas greatly improve the stroke matching ability of the selective stroke linkage method reported earlier by the authors. In experiments, only a single reference pattern for each of 2,980 Kanji character categories is generated by using training data composed of 120 patterns written carefully with the correct stroke-number and stroke-order. Recognition tests are made using the training data and two kinds of test data in the square style and in the cursive style written by 36 different people; recognition rates of 99.5%, 97.6%, and 94.1% are obtained, respectively. Moreover, comparative results obtained by the current OCR technique as applied to bitmap patterns of on-line character data are presented. Finally, future work for enhancing the stroke matching approach to cursive Kanji character recognition is discussed.