The objective of this study was to examine the feasibility of using a semiautomated computer-vision system to quantify the percentage of voids in mineral aggregates (VMA%) of bituminous mixtures. The system used a hybrid procedure which utilized a digital image analysis scheme and a planimeter surveying instrument. Thirty-nine Marshall specimens were prepared using limestone and gravel aggregates. Values of VMA% were obtained using the ASTM conventional procedure and the computer-vision procedure. To compute VMA% using the computer-vision procedure, normal case photography with uniform scale images was used to map horizontal and vertical cross sections of Marshall specimens. Image domain measurements were corrected for distortion. Spatial filters and image processing operations were used to enhance the aggregate edges. Experimental results showed slight variations between VMA% computed using conventional and the computer-vision procedures. The average differences of VMA% between conventional and the computer-vision procedures were 0.81% and 0.006% for gravel and limestone specimens, respectively. Measurements of VMA% for limestone mixtures were more precise than those for gravel mixtures because of the angular edge shape of limestone particles. Variations in VMA% were due to the anisotropic properties of asphalt mixtures, aggregate distribution in the asphalt mixture, and different shapes of aggregates. Using the computer-vision-based technique, VMA% of horizontal and vertical cross sections were 50% consistent. The existence of fine aggregate in the asphalt mixture affected the accuracy potential of the developed system because a low-resolution camera was used. Increasing the camera resolution and automating the area computation of aggregate are expected to enhance the potential accuracy of the procedure. The proposed method for VMA quantification is anticipated to improve field quality control of hot-mix asphalt (HMA). The use of computer-vision technology with bituminous mixtures can open the doors to a wide variety of applications.Key words: bituminous mixtures, voids in mineral aggregate, computer vision, automation, image processing.
معالي الأستاذ الدكتور محمد طالب عبيدات | HE PROF. Moh’d Taleb Obaidat | 7208