TY - JOUR
T1 - Portable image analysis system for characterizing aggregate morphology
AU - Wang, Linbing
AU - Lane, D. S.
AU - Lu, Yang
AU - Druta, Cristian
PY - 2009
Y1 - 2009
N2 - In the past decade, the application of image-based evaluation of particle shape, angularity, and texture has been widely researched to characterize aggregate morphology. Yet the lack of rapid, objective, and quantitative methods for assessment has inhibited its application in the engineering process. However, recent advances in technology have produced pocket computers with as much processing power as some desktop computers. This project takes advantage of these advances to develop an inexpensive portable image analysis system for characterizing aggregate morphology. The system uses an integral pocket computer-high resolution camera but can employ individual components consisting of a digital camera and a laptop or desktop computer. Digital images of coarse aggregate particles are captured with the camera and analyzed within the Matlab software program environment with a macro developed and written for this project to characterize particle morphology with respect to three parameters (shape, angularity, and texture) on the basis of the particle perimeter (outline or edge). For this purpose, several coarse aggregate types from 10 various Virginia sources were analyzed, and the reliability of the image processing was statistically assessed. Asymptotic analysis was performed to determine the number of images needed to obtain a statistically stable value for each aggregate parameter. It was determined that images acquired at close range (2 or 3 in.) were needed to provide sufficient resolution to adequately characterize the aggregates. Also, it was found that statistically valid values for the three aggregate parameters could be obtained from 15 particle images of random but stable orientation, thus making the system efficient in characterizing coarse aggregate morphology.
AB - In the past decade, the application of image-based evaluation of particle shape, angularity, and texture has been widely researched to characterize aggregate morphology. Yet the lack of rapid, objective, and quantitative methods for assessment has inhibited its application in the engineering process. However, recent advances in technology have produced pocket computers with as much processing power as some desktop computers. This project takes advantage of these advances to develop an inexpensive portable image analysis system for characterizing aggregate morphology. The system uses an integral pocket computer-high resolution camera but can employ individual components consisting of a digital camera and a laptop or desktop computer. Digital images of coarse aggregate particles are captured with the camera and analyzed within the Matlab software program environment with a macro developed and written for this project to characterize particle morphology with respect to three parameters (shape, angularity, and texture) on the basis of the particle perimeter (outline or edge). For this purpose, several coarse aggregate types from 10 various Virginia sources were analyzed, and the reliability of the image processing was statistically assessed. Asymptotic analysis was performed to determine the number of images needed to obtain a statistically stable value for each aggregate parameter. It was determined that images acquired at close range (2 or 3 in.) were needed to provide sufficient resolution to adequately characterize the aggregates. Also, it was found that statistically valid values for the three aggregate parameters could be obtained from 15 particle images of random but stable orientation, thus making the system efficient in characterizing coarse aggregate morphology.
UR - http://www.scopus.com/inward/record.url?scp=76649134800&partnerID=8YFLogxK
U2 - 10.3141/2104-01
DO - 10.3141/2104-01
M3 - Article
AN - SCOPUS:76649134800
SN - 0361-1981
SP - 3
EP - 11
JO - Transportation Research Record: Journal of the Transportation Research Board
JF - Transportation Research Record: Journal of the Transportation Research Board
IS - 2104
ER -