沥青混合料CT图像中粘连集料颗粒分离方法

为了准确分离沥青混合料CT(computerized tomography)图像内部的粘连集料颗粒,根据材料密度连续变化特点,对CT图像进行高斯平滑和H-maxima转换处理,消除图像噪音和降低图像内集料颗粒像素密度变异性,然后采用分水岭分割算法对沥青混合料CT图像内部粘连集料颗粒进行分割.确定分水岭分割后的集料颗粒尺寸参数,采用不同当量尺寸对集料颗粒级配进行虚拟筛分,对所提出的粘连集料颗粒分离方法进行筛分级配验证.结果表明:通过分水岭分割后的集料颗粒,采用等效直径作为当量尺寸进行级配虚拟筛分,结果与实际手工级配筛分结果吻合良好.该方法克服了以往研究中忽视对CT图像内部粘连集料颗粒的处理,是对计算机数字化设计沥青混合料级配的有益探索.

Adhesive Aggregate Particle Separation Approach for

In order to separate adhesive aggregate particles of asphalt mixture in CT(computerized tomography)images, based on the continuous density of the materials, the Gaussian smooth and H maxima transformation for CT images were performed to eliminate the noise and decrease the pixel density variability of aggregate particles in image, and then the watershed segmentation algorithm was used to segment the adhesive aggregate particles. The size parameters of aggregate particles segmented by watershed were determined. Furthermore, gradation of aggregate particles was virtually screened using different equivalent sizes, the method for segmenting adhesive aggregate particles was verified using screening gradation. The results show that the equivalent diameter can be regarded as equivalent size to conduct virtual gradation screening for aggregate particles segmented by watershed. The virtual gradation screening result for aggregate particles has good correlation with the actual gradation screening results. This method overcomes the defects of previous research ignoring to process the adhesive aggregate particles in CT images. It is a useful exploration for designing gradation of asphalt mixture digitally.