骨料(复合)
纹理(宇宙学)
沥青
计算机视觉
计算机科学
低分辨率
腐蚀
分辨率(逻辑)
人工智能
图像(数学)
地质学
材料科学
高分辨率
遥感
复合材料
古生物学
标识
DOI:10.1111/0885-9507.00191
摘要
The effect of fine aggregate morphologic properties on asphalt mixtures' behavior is well recognized. However, the current procedures for measuring fine aggregate properties are at best indirect indicators of these properties. The indirect nature of the current measurements has led to inconsistency in predicting the extent to which the measured properties influence pavement performance. Two independent methods that integrate several aspects of image‐analysis techniques are presented for quantifying angularity and texture of fine aggregates. The first technique relies on the change of aggregate shape as it is subjected to a number of erosion‐dilatation morphologic operations. The second technique uses the change of an object perimeter with its shape. The analysis shows that the two methods are able to capture aggregate shape at two different scales. Angularity is captured using low‐resolution images, whereas surface texture is captured using high‐resolution images. The presented image‐analysis techniques have potential benefit in quantifying the effects of texture and angularity on asphalt pavement performance.
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