The Influence of Incident Light Angles on Pilling Grading from Optical Image by Visual Assessment and Convolutional Neural Network

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Other Title
  • 視覚評価および畳み込みニューラルネットワークによる光学画像からのピリング等級判定における照明角度の影響

Description

<p>The influence of incident light angles and shadows on pilling grading was investigated. A pilling grade of fabric samples was evaluated from their images by visual assessments and by using a neural network. A series of images of a fabric sample was captured by changing the light-source angle with respect to a sample. Pilling grades of the images, even from the same fabric sample, was varied greatly according to the light-source angles. The greater the difference in angle, the greater the difference in grade. In addition, some samples were difficult to grade due to the light-source angle, therefore an angle of 15 or 30 degrees was considered to be appropriate for grading. The neural network was able to learn only with the low lightsource angle images that had clear shadows, and was able to predict the same level as experts in about 70％of the samples. Thus, the shadows were found to be an extremely important factor in recognizing pills for both humans and neural networks.</p>

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Details 詳細情報について

  • CRID
    1390010457641872640
  • DOI
    10.11419/senshoshi.63.4_250
  • ISSN
    18846599
    00372072
  • Text Lang
    ja
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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