繊維状粒子の顕微鏡画像解析のための2値化手法 A Binarization Technique for Microscopic Images Analysis of Fibrous Particles

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In processing microscopic images of fibrous particles, it is difficult to select adequate threshold value for binarization since the images usually have unimodal distribution of gray level. Inadequate threshold value brings undesirable spots on background or cut-off of fiber images. In this paper a new binarization technique was proposed, assuming that background had a normal gray level distribution and its capability was compared with two existing techniques, <I>i.e.</I>, the discriminant analysis and the neural network method. The experimental result showed that the neural network method gave the threshold value closest to that made by human judgement when the network learned adequately. Our proposed technique was second to the best. However, the discriminant analysis did not work well. Although the network has to learn again when the characteristics of images change beyond some allowable range, the criterion of the allowable range is not clear. Therefore, our proposed technique is the most practical one at present.

収録刊行物

  • エアロゾル研究 = Journal of aerosol research  

    エアロゾル研究 = Journal of aerosol research 10(4), 296-303, 1995-12-20 

    日本エアロゾル学会

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各種コード

  • NII論文ID(NAID)
    10002686815
  • NII書誌ID(NCID)
    AN10041511
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    09122834
  • データ提供元
    CJP書誌  CJP引用  J-STAGE 
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