Aggregate Image Measurement System Research Articles

Algorithm for Virtual Aggregates’ Reconstitution Based on Image Processing and Discrete-Element Modeling

Based on the Aggregate Imaging Measurement System (AIMS) and the Particle Flow Code in Two Dimensions (PFC2D), an algorithm for modeling two-dimensional virtual aggregates was proposed in this study. To develop the virtual particles precisely, the realistic shapes of the aggregates were captured by the AIMS firstly. The shape images were then processed, and the morphological characteristics of aggregates were quantified by the angularity index. By dividing the particle irregular shape into many triangle areas and adjusting the positions of the generated balls via coordinate systems’ conversion within PFC2D, the virtual particles could be reconstructed accurately. By calculating the mapping area, the gradations in two-dimensions could be determined. Controlled by two variables (μ_1 and μ_2), which were drawn from the uniform distribution (0, 1), the virtual particles forming the specimens could be developed with random sizes and angular shapes. In the end, the rebuilt model of the SMA-13 aggregate skeleton was verified by the virtual penetration tests. The results indicated that the proposed algorithm can not only model the realistic particle shape and gradations precisely, but also predict its mechanical behavior well.

Investigation on effects of different crushing stages on morphology of coarse and fine aggregates

ABSTRACTThe present study evaluates the effects of three different stages of crushing mechanism, namely two stage (2S), three stage (3S) and four stage (4S) on various morphology parameters (i.e. angularity, texture, flatness & elongation, sphericity and form2D) of aggregates. The 2S crushing consisted of primary and secondary crushers as Jaw and HSI (horizontal shaft impactor), respectively, while 3S crushing was composed of primary, secondary and tertiary crushers as Jaw, Jaw and HSI, respectively. In other word, 3S consisted of an additional jaw crusher compared to 2S crushing. Likewise, 4S crushing had primary, secondary, tertiary and quaternary crushers as Jaw, Jaw, HSI and VSI (vertical shaft impactor), respectively. The 4S had an additional VSI crusher to 3S crushing. Three coarse and three fine aggregate sizes were used in the study. A digital device, Aggregate Image Measurement System was used to measure various morphology parameters of aggregates and to assess the effects of stage crushing. The coarse aggregates were subjected to angularity, texture, sphericity and flatness and elongation, while fine aggregates were studied for angularity and form2D. A systematic statistical analysis was conducted to compare the mean value of aggregates shape parameters and draw logical conclusions. It was observed that effects of crushing on aggregate shape are a cumulative function of stage crushing, crushing mechanism and aggregate size. The outcome of the present study may be helpful in understanding effects of stage crushing mechanism on shape parameters of aggregates for quality production. Further, the study can assist in selection of an appropriate source of aggregate and crusher health monitoring via morphological characterisation of aggregates.

Pavement Analysis and Design by Multiphysics Reconstructing Algorithm for the Virtual Asphalt Mixture Based on the Discrete‐Element Method

Based on the Particle Flow Code in Two dimensions (PFC2D), an algorithm for modeling the two‐dimensional virtual asphalt mixture was proposed in this study. By combining the AIMS scanning technology (Aggregate Imaging Measurement System) with the designed stochastic algorithm, the virtual coarse aggregates could be generated rapidly and precisely. Different from the conventional methods, the contour shapes of the coarse aggregates were rebuilt only to balance the shape modeling precision and simulation efficiency. Then by distributing the coarse particles within container, virtual skeletons were formed firstly. An innovate algorithm was proposed afterwards to distinguish the external and internal area of the coarse aggregates and then model the mastic part by filling the irregular hollow shape with uniformly arranged balls. By deleting the mastic balls randomly, the voids were reconstructed consistent with the actual ratio. In the end, the virtual uniaxial compressive tests of AC‐16 were simulated within PFC2D and the dynamic modulus at different load frequencies was predicted. The results indicated that the proposed algorithm could not only model the asphalt mixture precisely but also characterized its mechanical behavior as well.

Kernel machines and firefly algorithm based dynamic modulus prediction model for asphalt mixes considering aggregate morphology

Artificial Intelligence algorithm support vector regression (SVR) has proved successful in outperforming conventional Witczak and ANN models for estimation of dynamic modulus (E∗) of asphalt mixes. However, there were two issues related to the development of E∗ prediction models that the present study addresses. Firstly, since aggregates occupy almost 95% by weight of HMA, it is quite possible that the morphology of these aggregates play an important role in influencing the E∗ values. To address this issue, aggregate shape parameters, namely, angularity, sphericity, texture and form were used with aggregate gradation for stiffness estimation. Secondly, to fine tune the hyper-parameters firefly algorithm (FA) was coupled with SVR. E∗ tests of 20 HMA mixes having different sources, sizes of aggregates, and volumetric properties were conducted at 4 temperatures and 6 frequencies. Aggregate shape parameters were measured using the automated aggregate image measurement system (AIMS). SVR-FA models were developed that predicted the E∗ with an R2 of 0.98. SVR-FA models were compared with SVR and ANN models for E∗ prediction. Further, a sensitivity analysis was conducted to identify the important input parameters. Lastly, an approach for formulation of SVR-FA model equations for direct prediction of HMA stiffness is also discussed. FA proved instrumental in improving the efficiency of SVR by optimizing the hyper-parameters with lesser manual effort. Finally, it was concluded that SVR-FA algorithm is capable of successfully predicting the E∗ values using the aggregate shape parameters.

Morphological characterization and mechanical analysis for coarse aggregate skeleton of asphalt mixture based on discrete-element modeling

Focused on the aggregate microstructures to characterize the aggregate mechanical properties, this paper proposed a modeling method of coarse aggregate based on the particle morphological characteristics. By using the Aggregate Image Measurement System (AIMS), the realistic shape of granular aggregates was captured and the statistical analysis was made to quantify the morphological differences firstly. Then by using Discrete-Element Method (DEM) software named as Particle Flow Code in two dimensions (PFC2D) and with the help of the image processing techniques, an algorithm was developed to model the two-dimensional shape of aggregates. Through linking the shape to the morphological index for each aggregate, the coarse aggregate skeleton was built which is consistent with the actual composition and structure of the laboratory specimens. After that, based on laboratory penetration test for granular aggregates, virtual penetration test was built by PFC2D to verify the validity of the developed modeling algorithm. An optimized method was proposed further then to improve the simulation efficiency. This is because of the time-consuming process when modeling the actual specimen which was composed of numerous coarse aggregates with various shapes. Some representative particles were selected and reconstructed based on the angularity index to form the virtual specimens with aggregates of gradations AC-13 and SMA-13. At last the virtual penetration test of AC-13, SMA-13 was conducted to predict the mechanical behavior and the coarse aggregate skeleton structure characteristics were analyzed from the point of micro-contact state. It is proved that the proposed modeling algorithm could well capture the realistic shape of aggregates and virtual test based on the aggregates model could characterize the granular aggregates mechanical properties accurately.

Understanding influence of crushers on shape characteristics of fine aggregates based on digital image and conventional techniques

Shape characteristics of fine aggregates, namely angularity and form 2D are greatly associated with the types of rocks, mineralogical compositions, and allied crushing mechanism. Thus, for a given source and aggregate, the type of crusher may play a critical role in producing aggregates having different shape parameters. The present study was undertaken to compare shape parameters of fine aggregates produced from three different crushers, i.e. vertical shaft impactor (VSI), cone crusher (CC) and horizontal shaft impactor (HSI). Basaltic fine aggregates collected from three different crushers was divided into five sizes, namely FA1 (P4.75-R2.36: aggregate passing 4.75mm and retaining on 2.36mm), FA2 (P2.36-R1.18), FA3 (P1.18-R0.600), FA4 (P0.600-R0.300) and FA5 (P0.300-R0.150). The angularity and form 2D values of different sizes and types of fine aggregates were measured using Aggregate Image Measurement System (AIMS) in accordance with AASHTO TP 81. Further, conventional technique namely fine aggregate angularity (FAA) test was used to measure angularity of fine aggregates. Furthermore, Angle of Repose (AoR) test was conducted to identify influence of shape characteristics on particle packing behaviour. The study showed that both the techniques (i.e., AIMS and FAA) could differentiate among the quality of fine aggregates produced from different crushers. However, both techniques resulted in opposite trend in angularity of aggregates. The AIMS measurement showed that angularity and form 2D was highest for aggregates produced from HSI crusher followed by CC and VSI. On the other hand, FAA showed that aggregates produced from CC crusher had maximum angularity followed by VSI and HSI. Conclusively, the AIMS showed that HSI crusher could produce aggregates with highest angularity, while FAA showed that this type of crusher might produce aggregates with least angularity. Curiously, the AoR values showed no significant difference for the fine aggregates produced from different crushers. The interrelation between angularity and form 2D is also discussed in the paper.

Accelerated laboratory testing of aggregate friction properties

Abstract This paper presents a thorough analysis of an experimental method for measuring aggregate friction properties. The second-generation Aggregate Image Measurement System (AIMS) is used to measure coarse aggregate surface texture before and after polishing in a modified Micro-Deval (MD) test procedure, in addition to Variable Speed Friction Test (VST) samples. Investigating the relationships between AIMS-MD angularity and texture, a weak relationship was found between VST friction values and AIMS angularity after MD polishing for 105 min (AMD-105). Furthermore, the strong correlation between AIMS AMD-105 texture and the surface texture of VST friction samples indicated that MD is a viable option for replacing VST as a polishing mechanism. Finally, cluster analysis was conducted to obtain threshold for classifying aggregate angularity and texture into acceptable and non-acceptable zones (i.e., defining the criteria for qualifying aggregates for friction purposes).

Evaluation of Two-Dimensional Gray-Scale Images for Microtexture Analysis of Aggregate Surface

AbstractA powerful texture feature extraction algorithm based on transform-based analysis of two-dimensional (2D) gray-scale images was employed in the aggregate image measurement system (AIMS) to quantitatively describe aggregate surface microtexture by way of a parameter called texture index (TI). TI has been used successfully to distinguish between unpolished and polished aggregates. The main goal of this research was to further evaluate this system using a broader range of aggregates in terms of mineral composition including highly uniform limestone sources and highly variable granitic sources. Results confirmed that TI successfully distinguished polished from unpolished aggregates for all mineral compositions. However, an excessively broad range of TI values was observed. Specifically, TI values of aggregates with highly variable mineral composition were far greater than any value previously reported in the literature. Interestingly, unusually high TI values were also observed for limestone aggregate...

Measuring skid resistance of hot mix asphalt using the aggregate image measurement system (AIMS)

Pavements need to have adequate structural, geometric and signaling conditions, in order to prevent accidents and to ensure safer transportation. In Brazil, asphalt pavement projects require proper volumetric and structural parameters, where as functional aspects, such as tire–pavement friction, are not always considered in the asphalt mixtures design. One of the most important factors in the tire–pavement friction is the asphalt mixes texture. In this context, the main objective of the present study is to evaluate a method for characterization of asphalt mixtures texture properties using digital image processing (DIP) techniques, demonstrating how these results can be correlated to the results of conventional tests and to the aggregate particles’ shape properties, such as angularity and surface texture. For this purpose, three hot mix asphalt (HMA) with different aggregate gradations and composed by aggregates with different shape properties were analyzed. Two HMA used in road pavements were produced, one with aggregate particles in their original form, and the other one with polished aggregate particles. The third mix was a HMA used in airport pavements, produced with non-polished aggregate particles. Besides these three mixes evaluated in the laboratory, four HMA used in the field were analyzed in order to compare the results obtained from the DIP, and the ones obtained using conventional texture and skid resistance tests. The results showed that the correlations between the HMA texture properties obtained using DIP and those obtained through conventional tests are not as good as expected. Moreover, the results indicated that the HMA particle size distribution directly affects its texture characteristics. Regarding the aggregate particles shape properties, it was found that small variations in these properties do not provide major variations in the results of HMA texture obtained by the DIP technique.

Virtual fabrication and computational simulation of asphalt concrete microstructure

This study presents the development and verification of an in-house microstructure generator that can be used to fabricate virtual, two-dimensional microstructures of asphalt mixtures. The proposed methodology takes advantage of a modern image analysis system, i.e. Aggregate Image Measurement System 2, to obtain geometric characteristics of real aggregate particles. During the generation process, images of real aggregates are stored in a database and further positioned in the virtual microstructures in a way that the gradation, area fraction and orientation of the virtual aggregate skeleton closely reproduce properties of real asphalt concrete samples fabricated in the laboratory. To demonstrate the capabilities of the generator, a microstructural analysis procedure used to quantify key volumetric characteristics of virtual samples is first proposed and verified. Then, using the verified analysis methodology, microstructural characteristics of virtual samples are determined and compared to those of real specimens. To further demonstrate the applicability of the proposed methodology, dynamic modulus simulations of virtually generated samples of asphalt concrete are performed using the finite element software ABAQUS and considering different aggregate characteristics. The results obtained indicate that the proposed methodology can be used as an efficient tool to fabricate and analyse virtual microstructures of asphalt concrete mixtures. This, in turn, becomes an essential step for the improvement of the computational microstructural model under development by the authors, which aims to accurately predict the mechanical behaviour of asphalt mixtures from known constituent properties and geometric characteristics, and to provide significant savings in the time and cost required for laboratory testing of actual specimens.

Aggregate Shape Properties and Their Influence on the Behavior of Hot-Mix Asphalt

Aggregate shape properties, such as form, angularity, and surface texture, highly influence the performance of hot-mix asphalt (HMA). Rutting is related to aggregate angularity and form, which affects the interlock among particles. Fatigue cracking can be decreased by an aggregate rough surface texture, which improves the aggregate-binder interaction. Several researchers have been studying new automated and more precise techniques, such as the aggregate image measurement system (AIMS), to improve the determination of aggregate shape parameters. This paper presents an analysis of aggregates from three different mineralogical sources, investigating the influence of shape properties on HMA design and mechanical properties. The results indicated that the aggregates had similar shape properties, despite differences in the mineralogical composition. This might be a direct effect of similar quarrying procedures. Surface texture resulted in different values, which can be explained by results from the petrographic analyses. In general, the aggregates’ shape properties resulted in HMA samples with similar mechanical behavior. The HMA specimens were also analyzed in terms of their internal structure, which included the investigation of a number of contact points, and aggregate particles’ segregation and orientation characteristics.

Experimental procedure for evaluation of coarse aggregate polishing resistance

This paper presents the development of experimental methods for measuring aggregate textural retention, which is a very important property that influences pavement skid resistance. The 2nd version Aggregate Image Measurement System (AIMS-II) is used to measure coarse aggregate surface texture before and after different polishing time intervals in a modified Micro-Deval (MD) test procedure. The use of AIMS-II to compare aggregate surface texture and the evolution of aggregate polishing curves was verified and determined to be successful because AIMS-II texture measurement closely reflected historical data on aggregate frictional properties obtained by Illinois Department of Transportation (IDOT). Analytical functions, considering aggregate surface texture at different polishing times, were then used to describe the initial texture, rate of polishing, and terminal texture. Statistical analysis was used to determine that the required polishing time to achieve terminal texture in the modified MD is 210min.

Evaluation of polishing and degradation resistance of natural aggregates and steel slag using the aggregate image measurement system

Aggregate resistance to polishing and degradation can be related to the change in some of those aggregates particles’ characteristics. Polishing resistance can be related to the loss of surface texture, and it can affect asphalt pavements’ microtexture, influencing its skid resistance. Degradation resistance is related to the loss of angularity and to the aggregates’ breakage. It affects pavement distresses’ resistance and aggregate gradation. The methodologies used to evaluate these characteristics produce results that are mostly not representative. This paper aims to present a digital image processing (DIP) technique to evaluate aggregates’ resistance to polishing and degradation, along with the use of the Los Angeles abrasion equipment. The aggregate image measurement system was used to analyse the aggregates mainly not only with respect to angularity and surface texture, but also with respect to sphericity and flatness/elongation particle percentage, before and after the polishing and the degradation processes. Three natural aggregates (granite, gneiss and phonolite) collected from Brazilian quarries, and one by-product (steel slag) were evaluated. The findings from this study can be used to rank aggregates with respect to their shape properties. With the results obtained for the steel slag, it can be concluded that this material was the most resistant to polishing when compared with the natural aggregates.

Effect of production and sample preparation methods on aggregate shape parameters

The performance of hot mix asphalt (HMA) greatly depends upon the aggregate shape characteristics, namely angularity, two-dimensional (2D) form, texture and sphericity. This paper presents the effect of plant production and sample preparation methods on the shape characteristics of coarse aggregate (CA) and fine aggregate (FA). Six different types of aggregates, namely original aggregate (OA), plant mix (PM) aggregate and aggregate retrieved from specimens compacted at four different air voids [6% (AV6), 8% (AV8), 10% (AV10) and 12% (AV12)] were used. Each type of aggregate was divided into two different sizes: coarse and fine. The sizes of CAs were passing a 19 mm sieve and retained on a 12.5 mm sieve (CA12), and passing a 9.5 mm sieve and retained on a 4.75 mm sieve (CA4). Similarly, the sizes of FAs were passing a 4.75 mm sieve and retained on a 2.36 mm sieve (FA8), and passing a 2.36 mm sieve and retained on a 1.18 mm sieve (FA16). The Aggregate Image Measurement System was used to measure the shape characteristics of each size of aggregate. A statistical method called analysis of variance was used to compare the mean of shape parameters. The analyses of the results indicate that the texture and 2D form of CA particles change significantly when they undergo different processes of HMA production and sample preparation. No significant difference was observed in angularity and sphericity for all types of CAs. Similarly, no significant changes were observed in FA shape parameters. The effect of aggregate size on the shape parameters is also discussed. It is expected that the present study would develop a better understanding of HMA mixture behaviour in light of aggregate properties pertaining to aggregate shape.

Evaluation of Aggregate Imaging Techniques for Quantification of Morphological Characteristics

Aggregate morphological characteristics, including shape, angularity, and surface texture, have a significant impact on the engineering properties of construction materials such as hot-mix asphalt and hydraulic cement concrete. Consequently, the quantification of morphological characteristics of aggregates is essential for quality control of both aggregate production and pavement construction. Imaging techniques provide a cost-effective means for measuring the aggregate morphological characteristics conveniently without tedious work. However, these imaging techniques adopt various mathematical methods with different instrument setups and result in different definitions of morphological descriptors that are usually incomparable with each other. This paper evaluates prevalent imaging techniques used for aggregate morphological characteristics analysis, including equipment cost, repeatability, reliability, accuracy, and measured morphological parameters. Three imaging techniques (second-generation Aggregate Imaging Measurement System, first-generation University of Illinois aggregate image analyzer, and Fourier transform interferometer system), are further evaluated by comparing the analysis results of seven types of aggregates passing a ¾-in. sieve and retained on a ½-in. sieve with manual measurements and visual rankings. Analysis of variance between measurements using different methods is also conducted to evaluate the accuracy of each aggregate imaging system. From the data analysis, recommendations that depend on morphological characteristics of most interest to engineers are made for the selection of appropriate imaging-analysis techniques.

Inclusion of aggregate angularity, texture, and form in estimating dynamic modulus of asphalt mixes

The present study was undertaken to develop a model that utilizes aggregate shape parameters (i.e. angularity, texture and form) in estimating the dynamic modulus of asphalt mixes. Dynamic modulus tests were conducted on 20 different mixes comprised of different aggregate sources, sizes, asphalt binder, and air void levels. The coarse and fine aggregates were recovered from each mix, and their shape parameters were measured using an automated aggregate image measurement system (AIMS). A nonlinear regression model was developed to estimate the dynamic modulus of the mix in terms of its aggregate gradation, aggregate shape parameters, viscosity of asphalt binder, and volumetric properties. The correlation coefficient (R 2) for the developed model was found to be 0.95 and 0.92 on logarithmic and arithmetic scales, respectively, with a mean average relative error (MARE) of 21.9%. The performance of this model was compared with the widely accepted Witczak model that does not use the shape parameters of the aggregates. The MARE for the Witczak model was estimated significantly higher than the developed model. Results show that the dynamic modulus of the mix increases with an increase in the angularity and texture of aggregates and that the inclusion of shape parameters can enhance the prediction capability of a model.

Comparison of Shape Parameters for Selected Coarse Aggregates in Oklahoma

Abstract The performance of pavement can be significantly influenced by the gradation and shape parameters of the aggregates (i.e., angularity, texture, form, and sphericity). An accurate measurement of these properties is important for the development of specifications for the quality control and quality assurance of aggregates. The present study was undertaken in order to compare the shape parameters of different types and sizes of selected coarse aggregates that are commonly used in Oklahoma. Three different types of aggregates—granite, rhyolite, and limestone—were collected from stockpiles. Each type of aggregate was divided into three different sizes of coarse aggregates. These sizes include the following: passing through a 19 mm sieve and retained on a 12.5 mm sieve (CA1), passing through a 12.5 mm sieve and retained on a 9.5 mm sieve (CA2), and passing through a 9.5 mm sieve and retained on a 4.75 mm sieve (CA3). CA1 type aggregates had the largest size, followed by CA2 and CA3. An automated aggregate imaging measurement system was used to measure the shape parameters of the aggregates. The results show that the aggregates become smooth (low texture) and elongated (high form and low sphericity) as their size decreases. No relation was observed between the particle size and the angularity of the aggregates. A comparison of different types of aggregates indicated that, in general, granite aggregates were highly rough (high texture) and cubical (low form and high sphericity) compared to rhyolite and limestone aggregates. Similarly, the angularity of granite aggregates was found to be significantly different than that of rhyolite and limestone aggregates. The ranking of the aggregates was done based on the composite shape index factor (CI) for angularity, form, texture, and sphericity. The CI considers the combined effect of the gradation and shape parameters of aggregates. In addition, the ranking of aggregates was further verified by estimating the dynamic modulus (|E*|) of the mixes composed of granite, rhyolite, and limestone aggregates. The aggregate shape-based model developed by the authors was used to estimate |E*| of a mix using the aggregate shape parameter, frequency, viscosity of the asphalt binder, and volumetric properties of a mix. |E*| of a mix is considered as an important parameter in estimating the performance of flexible pavements in terms of fatigue, rutting, and low temperature cracking. Therefore, the ranking of aggregates based on |E*| of the mixes provides a better understanding of the performance of the aggregates. The results show that both methods for ranking the aggregates (i.e., CI factor and |E*|) showed similar results. Overall, the mix with rhyolite aggregate was ranked first, followed by the mixes with limestone and granite aggregates.

Image Analysis Technique for Aggregate Morphology Analysis with Two-Dimensional Fourier Transform Method

This paper presents some results of the NCHRP 4–34 Laser Detection and Ranging project. A high-resolution Fourier transform interferometry (FTI) system was developed for aggregate morphology characterization with the use of a fiber-optic coupler to form a Young's double-pinhole interferometer. The FTI system used a charge-coupled device camera to capture fringe images of aggregates with a size ranging from ¾ in. to No. 50 and to reconstruct three-dimensional surfaces of aggregates on the basis of fringe distortions from the captured digital images. A program was developed in MATLAB to quantify morphologic characteristics of aggregates from a variety of sources. The output results include sphericity, flatness ratio, elongation ratio, angularity, and texture for each individual aggregate particle. In this paper, only the morphologic characteristics of seven types of coarse aggregate with sizes ranging from ¾ in. to No. 4 are presented. These aggregates were also analyzed with the Aggregate Image Measurement System (AIMS) II and the University of Illinois aggregate image analyzer (UIAIA) for further comparison. The FTI system is easy to operate and can rapidly quantify morphologic characteristics of aggregates. The FTI results of these aggregates are generally consistent with the results of AIMS II and UIAIA with regard to roughness rankings despite minor differences for several aggregates.

Simple Laboratory Method for Measuring Pavement Macrotexture

Pavement surface friction influences traffic accident rates, especially during wet weather, and is affected by pavement surface texture as characterized by microtexture and macrotexture. This study investigated the utility of measuring pavement surface macrotexture in the laboratory by using the aggregate image measurement system (AIMS) on cores extracted from pavement sections. Texture measurements made in the laboratory with AIMS were compared with texture measurements made on the pavement with the circular track meter (CTMeter). Previous research established a strong correlation between the mean profile depth (MPD) from the CTMeter, which considered averages of maximum heights, and the mean texture depth from the sand patch test, a volumetric method that was the accepted standard for macrotexture measurement. Similarly, in this study, statistical analysis showed a good correlation between the MPD values from AIMS measurements on pavement cores, based on analysis with 50-mm (2-in.) scan line segment lengths, and the MPD measured on the pavement in the field with the CTMeter. Further analysis using root-mean-square (RMS) values that considered all height measurements showed that the proposed procedure with AIMS was sensitive to the direction of the texture measurement scans and could therefore distinguish traffic direction across the core. The mean RMS values from AIMS also had a fairly strong relationship with the MPD values measured on the pavement by the CTMeter. Finally, the results indicated that a set of three directional scan lines could be used on the cores instead of four directional scan lines and the conclusions were still valid.