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An automated method for detecting flaky and elongated aggregates and gradation in a contacting state using integrated image and point cloud data
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DOI：10.1016/j.conbuildmat.2026.147652.png)
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Abstract
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• Image-point cloud fusion separates contacting aggregate particles. • Mask R-CNN and Zernike moments enable subpixel aggregate boundaries. • Standard-block calibration maps image boundaries to point clouds. • Gradation errors were below 3% for 4.75–31.5 mm aggregates. • Flaky and elongated aggregate recognition exceeded 92% accuracy.
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