A volumetrics thresholding algorithm for processing asphalt concrete X-ray CT images

This paper presents an automated digital image processing technique for capturing the microstructure of asphalt concrete (AC) from X-ray computed tomography images. It applies to circular cross-section images of AC cores of known volumetrics. Its innovation is that it uses the volumetric properties as the main criterion for establishing grey-level thresholds for the boundaries between air–mastic and mastic–aggregates. The algorithm, implemented in MATLAB™, involves three stages. The first stage involves image pre-processing for contrast enhancement and noise removal. The second stage is the main thresholding routine accepting as input the enhanced images of the first stage and volumetric information for the AC. It consists of two components, namely volumetrics-driven thresholding and 3D representation/sectioning. The third stage further enhances particle separation through edge detection and image segmentation. Examples were provided in imaging actual AC cores of known volumetric properties. The algorithm was shown to produce realistic rendering of the microstructure of ACs. Their quality is suitable for input into numerical simulation.

[1]  Larry N. Lynch,et al.  Morphological Study of Coarse Aggregates Using Image Analysis , 1998 .

[2]  Thomas Harman,et al.  Quantifying Laboratory Compaction Effects on the Internal Structure of Asphalt Concrete , 1999 .

[3]  Carl T. Haas,et al.  A PROTOTYPE LASER SCANNER FOR CHARACTERIZING SIZE AND SHAPE PARAMETERS IN AGGREGATES , 2001 .

[4]  Leslie George Tham,et al.  Finite element modeling of geomaterials using digital image processing , 2003 .

[5]  A. T. Papagiannakis,et al.  Micromechanical Analysis of Viscoelastic Properties of Asphalt Concretes , 2002 .

[6]  Roman D. Hryciw,et al.  Soil Particle Size Distribution by Mosaic Imaging and Watershed Analysis , 1999 .

[7]  Jian-Shiuh Chen,et al.  Evaluation of internal resistance in hot-mix asphalt (HMA) concrete , 2002 .

[8]  Eyad Masad,et al.  AGGREGATE ORIENTATION AND SEGREGATION IN ASPHALT CONCRETE , 1998 .

[9]  Hussain U Bahia,et al.  MODELING AND EXPERIMENTAL MEASUREMENTS OF STRAIN DISTRIBUTION IN ASPHALT MIXES , 2001 .

[10]  Marco Foi,et al.  Characterisation of Mortar Morphology in Thin Sections by Digital Image Processing , 2005 .

[11]  John D'Angelo,et al.  X-ray Tomography to Characterize Air Void Distribution in Superpave Gyratory Compacted Specimens , 2002 .

[12]  Eyad Masad,et al.  Three dimensional simulation of fluid flow in X‐ray CT images of porous media , 2004 .

[13]  Petra Offrell,et al.  In Situ Photographic Survey of Crack Propagation in Flexible Pavements , 2004 .

[14]  E. Masad,et al.  Internal structure analysis of asphalt mixes to improve the simulation of Superpave gyratory compaction to field conditions , 2001 .

[15]  Thomas Harman,et al.  PROPOSED METHODOLOGY FOR PREDICTING HMA PERMEABILITY (WITH DISCUSSION) , 2002 .

[16]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[17]  Richard M. Leahy,et al.  Determination of Internal Deformation Field in Asphalt Cores Using X-Ray Computer Tomography , 1996 .

[18]  Reed B. Freeman,et al.  Image Analysis Evaluation of Aggregates for Asphalt Concrete Mixtures , 1998 .

[19]  Eric N. Landis,et al.  X-ray microtomography for fracture studies in cement-based materials , 1999, Optics & Photonics.

[20]  S. Y. Wong,et al.  Quantification of movements of flat and elongated particles in hot mix asphalt subject to wheel load test , 2005 .

[21]  Eyad Masad.  REVIEW OF IMAGING TECHNIQUES FOR CHARACTERIZING THE SHAPE OF AGGREGATES USED IN ASPHALT MIXES , 2001 .

[22]  C. Chandan,et al.  Application of imaging techniques to geometry analysis of aggregate particles , 2004 .

[23]  Eyad Masad,et al.  Internal Structure Characterization of Asphalt Concrete Using Image Analysis , 1999 .

[24]  Joe W Button,et al.  Unified Imaging Approach for Measuring Aggregate Angularity and Texture , 2000 .

[25]  Eyad Masad,et al.  Spatial and Directional Distribution of Aggregates in Asphalt Mixes , 2002 .

[26]  Jong Won Park,et al.  Connectivity-based local adaptive thresholding for carotid artery segmentation using MRA images , 2005, Image Vis. Comput..

[27]  Eyad Masad,et al.  CHARACTERIZATION OF AIR VOID DISTRIBUTION IN ASPHALT MIXES USING X-RAY COMPUTED TOMOGRAPHY , 2002 .

[28]  Andreas E. Savakis,et al.  Adaptive document image thresholding using foreground and background clustering , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

[29]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[31]  S. Pizer,et al.  The Image Processing Handbook , 1994 .

[32]  Naga Shashidhar,et al.  X-Ray Tomography of Asphalt Concrete , 1999 .

[33]  J. S. Lai,et al.  Three-Dimensional Digital Representation of Granular Material Microstructure from X-Ray Tomography Imaging , 2004 .

[34]  Márcio Portes de Albuquerque,et al.  Image thresholding using Tsallis entropy , 2004, Pattern Recognit. Lett..

[35]  Jong Bae Kim,et al.  Multiresolution-based watersheds for efficient image segmentation , 2003, Pattern Recognit. Lett..

[36]  Mark R. Lankton,et al.  Assessment of localized deformations in sand using X-ray computed tomography , 2000 .

[37]  Alina N. Moga,et al.  An efficient watershed algorithm based on connected components , 2000, Pattern Recognit..

[38]  Jaime Reyes.  Quantifying the Role of Coarse Aggregate Strength on Resistance to Load in HMA , 2007 .

[39]  SoillePierre,et al.  Watersheds in Digital Spaces , 1991 .

[40]  T Harman,et al.  Characterization of aggregates and asphalt concrete using x-ray computerized tomography: a state of the art report , 2004 .

[41]  Paulo Estevão Cruvinel,et al.  X-ray microtomography to characterize the physical properties of soil and particulate systems , 1999 .

[42]  Carl T. Haas,et al.  3D Image Segmentation of Aggregates from Laser Profiling , 2003 .

[43]  Jian-Shiuh Chen,et al.  Quantification of Coarse Aggregate Shape and Its Effect on Engineering Properties of Hot-Mix Asphalt Mixtures , 2001 .

[44]  Hong Zhang,et al.  A multistage adaptive thresholding method , 2005, Pattern Recognit. Lett..

[45]  A. Persson,et al.  Image analysis of shape and size of fine aggregates , 1998 .

[46]  Paul L. Rosin.  Unimodal thresholding , 2001, Pattern Recognit..

[47]  Erol Tutumluer,et al.  Evaluation of image analysis techniques for quantifying aggregate shape characteristics , 2007 .

[48]  L. Banta,et al.  Estimation of limestone particle mass from 2D images , 2003 .

[49]  D. M. P. Hagyard,et al.  Analysis of watershed algorithms for greyscale images , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[50]  Zhong Qi Yue,et al.  APPLICATION OF DIGITAL IMAGE PROCESSING TO QUANTITATIVE STUDY OF ASPHALT CONCRETE MICROSTRUCTURE , 1995 .

[51]  Joe W Button,et al.  Implications of Experimental Measurements and Analyses of the Internal Structure of Hot-Mix Asphalt , 2004 .