CRACK DETECTION FROM EXTERNAL WALLS OF NATURAL STONES USING DEEP CONVOLUTIONAL NEURAL NETWORK

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  • SUZUKI Aiga
    Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST) Graduate School of Science and Technology, Univ. of Tsukuba
  • YANAGIMOTO Takashi
    Technology Center, Taisei Corporation
  • NAKAMURA Ryohei
    Technology Center, Taisei Corporation
  • SAKAMOTO Shigehiro
    Technology Center, Taisei Corporation
  • SAKANASHI Hidenori
    Artificial Intelligence Research Center, AIST Graduate School of Science and Technology, Univ. of Tsukuba

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  • 深層畳み込みニューラルネットワークによる建物外装石材画像からのひび検出

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Abstract

<p>Early detection of the crack in the external wall is a critical task in building maintenance. An image-based inspection has an advantage in terms of cost and efficiency; however, it requires much effort for high-rise buildings because of a massive number of taken pictures. Specifically, it is hard to distinguish the cracks in the walls made of natural stones from their complex texture pattern. To support such inspection, we developed the artificial-intelligence-based computer-aided detection system for wall cracks. We demonstrated that the system detects cracks properly in pictures of granite wall panels taken from a real tower building.</p>

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