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A neural network algorithm for detecting invisible concrete surface cracks in near-field millimeter-wave images

Using near-field millimeter-wave imaging, we have developed a nondestructive inspection tool called “Crack Scan” to detect concrete surface cracks of sub-millimeter width. In this paper, we propose a new image-processing algorithm based on a cross-coupled neural network, which enables Crack Scan to detect invisible cracks in blurred images. We demonstrate that our algorithm can detect a 0.2-mm-wide crack under a ceramic tile on-site.