用实验图像和堆积角估算港口散货堆体积，精度高。
Validation of Dry Bulk Pile Volume Estimation Algorithm based on Angle of Repose using Experimental Images
- 基于堆积角和轮廓检测重建3D模型估体积
- 对锥形和长条形堆体均实现高精度估计
- 适合港口物流与遥感体积监测场景
港口散装货物堆体体积估算在物流管理中至关重要，有助于优化船舶调度与航线规划，提升整体运营效率。本文验证了一种基于远程传感图像的干散货堆体体积估算算法。该方法通过实验室获取的图像先检测堆体轮廓，再结合物料堆积角重建三维模型并计算体积。我们在完整锥形堆、单脊长条堆以及修复后的锥形和长条堆上进行了验证，并进一步测试了其在参考卫星图像上的表现。结果表明，该算法在实验图像及参考卫星图像上均展现出高精度，具备准确估算堆体体积的潜力。
原文摘要 · Abstract (English)
Estimation of volume of piles in shipping ports plays a pivotal role for logistics management, facilitates better ship rescheduling and rerouting for economic benefits and contributes to overall efficient shipping management. This paper presents validation results for a volume estimation algorithm for dry bulk cargo piles stored in open ports. Using remote sensing images obtained in a laboratory setting, the method first detects the contour of the pile and then reconstructs its 3D model based on the material's angle of repose, and estimates the volume accordingly. We validated the algorithm on full conical piles and single-ridge elongated piles, and further tested it on reclaimed conical and elongated piles. The results demonstrated the algorithm's strong potential for accurately estimating pile volume from experimental images and a reference satellite image, achieving high accuracy in our validation.
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