Real-Time Image Thresholding Based on Sample Space Reduction and Interpolation Approach

Real-time thresholding is very essential for real-time processing. In this paper, we use pavement crack detection as an example to explain the principle of the proposed approach. Conventional visual and manual analysis approaches to pavement crack detection are very costly, time-consuming, labor-intensive, and subjective. Real-time automated detection of pavement cracks will be very useful for pavement management. We employ the proposed sample space reduction and interpolation approach for thresholding pavement images. The main idea of the proposed approach is based on the fact that the threshold values of gray-level pavement images are strongly related with the values of the mean and standard deviation of the pixel intensities. The experimental results have demonstrated that the proposed approach can determine the threshold values accurately, reliably, robustly, quickly, and automatically. It can be applied to other real-time processing tasks as well.     

In Field Soil Characterization: Approach Based on Texture Image Analysis

Building on the development of a tool for in place soil investigation based on the use of endoscopy, this paper presents a method for soil characterization using the images recorded by this tool. Various techniques have been explored including texture analysis which is very attractive because it is based on global image analysis. The use of a third order moment resulting from spectral analysis and its value for soil characterization is presented. The influence of various parameters (particle size distribution, mineralogy, water content, and compaction) on the moment evolution is studied.     

Particle Image Velocimetry System with Self-Organized Feature Map Algorithm

Self-organized feature map algorithm and the classical particle tracking technique have been adopted together to analyze the single-exposure double-frame particle images for flow measurement. Similar to the normal correlation technique in particle image velocimetry, the whole region is divided into many small interrogation spots. Instead of applying the correlation algorithm to each of these spots to obtain their rigid translation, the self-organized feature map algorithm is used to compress the information such that every spot is represented by three coded equivalent particles. After tracking these three particles, a linear distributed velocity function can be obtained at every spot. The spot can contain not only translation, but also rotation, shear, and expansion while there is only rigid translation in the spot assumed in the commonly used correlation method. In addition to the theoretical explanation, the suggested method has been verified by a number of digital flow fields which have randomly distributed synthetic particles.     

Adaptive Cross Correlation for Imaging Displacements in Soils

Digital image correlation (DIC) is used in this paper to study two-dimensional spatial soil deformations nonintrusively. Adaptive cross correlation (ACC), which is an advanced cross-correlation algorithm that utilizes variable window sizing and window shifting methods, was used to reduce the errors associated with conventional DIC. Comparison of the two algorithms using a scheme of predefined digital and physical movements shows that ACC improves the accuracy and range of DIC. A model of a strip footing on sand is presented. A digital camera was used to capture consecutive images of soil deformations through a Plexiglas mold. The spatial deformation of the soil beneath the footing was obtained by correlating consecutive images using ACC. Shear strains and the failure surface were also calculated based on the displacements measured using ACC. The optical setup and digital image processing technique presented in this paper were proven to be an effective tool for studying soil–structure interaction nonintrusively.     

Urban Damage Estimation Using Statistical Processing of Satellite Images

Remotely sensed satellite imagery of an earthquake-affected region can significantly assist in estimating the severity of infrastructure damage. Modern high-resolution satellite systems have been launched to provide users optical imagery with submeter accuracy, which enable the possibility of sensing damage for individual structures by means of pre- and postevent imagery. Recognizing these advancements, herein, we focus our study on the region of Bam, Iran, which was devastated by a moment magnitude Mw = 6.6 earthquake on December 26, 2003, causing approximately 43,200 lives lost. The recognition of urban structures within the Bam region is obtained by performing morphological filtering and intensity thresholding, which is further optimized through a statistical procedure. By overlaying the recognized structures with the pre- and postevent images, three object-based change detection methods are presented. The performance of change indices resulting from the three change detection methods is evaluated by means of a histogram-based classification approach. Damage estimation results are presented using easily interpretable maps, wherein individual structures are rendered with colors representing the severity of damage.     

Accuracy of Digital Image Correlation for Measuring Deformations in Transparent Media

Experimental models to measure spatial deformation patterns within a soil mass are typically limited by the fact that soil sensors do not provide a continuous image of the measured continuum. Additionally, soil sensors exhibit static and dynamic characteristics that are different from those of the surrounding soils and therefore can change the response of the measured continuum. The fundamental premise of this research is that transparent synthetic soil surrogates can be used to overcome these difficulties using digital image correlation (DIC). A system consisting of a laser source and a line-generating lens was used to optically slice the transparent synthetic soil models. A digital camera was used to capture images of the slices before and after deformation. This paper presents a new technique for quantifying spatial deformation throughout transparent synthetic soil models using DIC. The accuracy of the DIC technique was evaluated based on a scheme of predefined digital movement of synthetic soil images. Finally, a model consisting of a strip footing on a synthetic transparent soil is presented. The spatial deformations in the model are evaluated using the proposed DIC methodology and compared with the result of finite-element analysis.     

Vertical Stiffness and Deformation Analysis Models of Rubber Isolators in Compression and Compression-Shear States

The vertical stiffness and deformation theories of rubber isolators in compression and compression-shear states are systemically researched in the paper, a series of basic concepts, such as origin compression stiffness, origin compression longitudinal elastic modulus, offset vertical stiffness, etc. are suggested with corresponding theoretical formula and experimental estimation method. Based on the basic concepts and newly suggested calculating theories, the deformation calculating theory related to pure compression state and compression-shear state of isolating bearing is established. The vertical stiffness, offset vertical stiffness and deformation tests are performed with nature rubber bearings and lead plug rubber bearings total 16 original specimens to verify the new concepts and computation model of rubber isolators. All test results show that the theories established in the paper are suitable for analyzing the vertical stiffness and deformation of rubber isolators.     

Digital Image Analysis to Determine Pore Opening Size Distribution of Nonwoven Geotextiles

The filtration performance of a geotextile is controlled by its pore opening size distribution (PSD). Current methods for determining PSD are mostly indirect and contain inherent disadvantages. Recent technological advancements in image analysis offer great potential for a more accurate and direct way of determining the PSD of nonwoven geotextiles. A new and accurate method of image analysis for PSD determination of nonwoven geotextiles is presented in this paper. The image analysis method was developed using various mathematical morphology algorithms to provide a complete PSD curve for each geotextile. The two characteristic pore opening sizes, O95 and O50, were determined from image analysis and were compared to the results from laboratory tests, analytical equations, as well as manufacturer’s reported apparent opening sizes (AOS). The image-based O95 pore opening size of various geotextiles was comparable to the manufacturer’s reported AOS as well as to those determined from the laboratory dry sieving test. However, the measured O50 pore opening size was lower than the one determined using the analytical equations developed by two previous researchers. Overall, the image analysis method presented provides a unique and accurate method that can measure fiber thickness and pore opening sizes in a cross-sectional image of a woven geotextile.     

Simultaneous Particle Image Velocimetry and Laser Doppler Velocimetry Measurements of Periodical Oscillatory Horseshoe Vortex System near Square Cylinder-Base Plate Juncture

This paper presents simultaneous measurements using particle image velocimetry (PIV) and laser Doppler velocimetry (LDV) techniques on the study of a horseshoe vortex system. The horseshoe vortex system is generated near the juncture of a vertical square cylinder and a horizontal base plate. The combination of PIV and LDV not only gives the spatial distribution and time history of velocity near the juncture for spatial and time domain analyses, it also allows phase averaging the PIV velocity data to reduce noise and, in a turbulent flow, result in turbulence statistics. A flow visualization technique displaying particle streaklines has also been used to help the classification of the vortex system and visualize the flow motion and vortex evolution. The classification of the horseshoe vortex was briefly categorized as steady, periodical oscillatory, and turbulence-like chaotic vortex systems through the use of the flow visualization technique and time-domain spectral analysis. Phase-averaged flow characteristics of the periodical oscillatory vortex system with a Reynolds number of 2,250 are presented in detail through the use of PIV and LDV as well as the flow visualization technique.     

Image Analyses-Based Nondisruptive Method to Quantify Algal Growth on Concrete Surfaces

A global ban on the use of tributyltin has resulted in the need to screen new antifouling agents to control algal growth in aquatic environments. Standard methods for the quantification of algal biomass are disruptive in nature; therefore, they are not applicable for the screening studies requiring successive observations at specified time intervals. The objective of this study was to develop a nondisruptive method to quantify algal growth on a variety of surfaces. Image analyses and chlorophyll extraction methods were used to quantify an algal biomass on a concrete surface containing different additives. For concrete samples containing single additives, the coefficient of determination between both techniques ranged from 0.74 to 0.84. However, for concrete samples containing multiple additives, the coefficient of determination of both methods ranged from 0.72 to 0.75. Results suggest that an image analyses technique can be used to accurately quantify various types of algae growing on a variety of solid surfaces.     

TAX: Prototype Expert System for Terrain Analysis

Terrain analysis is a time‐consuming, costly, and labor‐intensive process requiring special skills and training. Furthermore, an enormous amount of remotely sensed data is routinely generated by satellite and airborne sensors which can be used for terrain analysis. Thus, there is an urgent need for an automated approach to analyzing these data and model human reasoning. A rule‐based expert system methodology has been developed and the Terrain Analysis Expert (TAX) has been implemented for modeling interpretation logic involved in identifying landforms from aerial images. Knowledge about the geographic location of the image was used to arrive at hypotheses about the landform of the site manifested on the aerial image. These hypotheses were then established or rejected based on the degree of match between the hypothesized landform's pattern elements and those of the site. The site was declared to be the landform with which it had the best match. The pattern elements of the site were obtained interactively from the analyst. A probabilistic method was designed for handling uncertainties in the observed pattern element values and their role in the identification of landforms. The results indicated that a rule‐based expert system is appropriate for representing image interpretation logic involved in terrain analysis.     

Combined Particle Image Velocimetry/Planar Laser Induced Fluorescence for Integral Modeling of Buoyant Jets

Combined particle image velocimetry and planar laser induced fluorescence is an efficient measurement approach for laboratory studies in environmental hydraulics. The coupling of the two well-known techniques enables synchronized planar measurements of flow velocity and concentration in an area yielding both their mean distribution as well as turbulence covariance. In this paper, the merits and limitations of the combination are first discussed. An example of experimental setup is then briefly described. Finally, an application is demonstrated for the integral modeling of an inclined round buoyant jet that takes full advantage of the capability of the combined approach.     

Damage Evaluation with P-Wave Velocity Measurements during Uniaxial Compression Tests on Argillaceous Rocks

In the study of time dependent behavior of rock, the main difficulty is to predict delayed failure, which is of the utmost importance in assessing the safety of underground structures, such as deep underground facilities designed for high-level radioactive waste disposal. In this context, the viscoplastic behavior associated with the rock damage must be taken into account. As the longitudinal and transversal wave velocities are related to the physical and mechanical characteristics of materials, ultrasonic measurements can give valuable information about the development of damage. In this study, P-wave velocity measurements were used to monitor damage evolution during uniaxial strain in controlled compression tests and long-term creep tests. These measurements were performed using sensors in a piezoelectric copolymer of polyvinyl-difluoride, which were placed on both ends of cylindrical rock specimens. Throughout the experiments, the dilating behavior of an argillite could be correlated with a decrease of the P-wave velocity. Our results show that during a creep test, P-wave velocity measurements allow the three different phases of creep to be distinguished. During primary creep the P wave increases because of pore closure. The secondary creep phase, characterized by a constant strain rate, is identified by a linear decrease of the wave velocity; this trend accelerates during tertiary creep.     

Dimensional Analysis of Bridges from a Single Image

Dimensional analysis from single images is still a fruitful topic for investigation, even if range sensors and stereo imaging technologies are becoming a common alternative to the generation of metric information. This paper describes the scientific approach developed for the dimensional analysis of bridges based on a single image. The basic dimensions of bridges are provided using a low-cost and flexible alternative that breaks with the classical stereoscopic photogrammetric principle. Several case studies are reported to demonstrate the novelty and real capabilities of this methodology.     

Large Scale Particle Image Velocimetry for Low Velocity and Shallow Water Flows

Large scale particle image velocimetry (LSPIV) is an extension of quantitative imaging techniques for measurements of water surface velocities using inexpensive standard video equipment. The present Technical Note describes capabilities and limitations of LSPIV for low velocity shallow flows. Measurements in low velocity shallow flume flows were performed to investigate the LSPIV sensitivity to seeding density and time interval between successive images. The results show that the accuracy of the LSPIV technique does not deteriorate as the flow velocity is reduced to as low as 0.015 m/s provided an adequate seeding and suitable time difference between images are selected. The results suggest that LSPIV is well-suited for flow fields with small velocities that are often below the limit of detection of most conventional devices.     

Validation and Extension of Image Velocimetry Capabilities for Flow Diagnostics in Hydraulic Modeling

In the last 3 decades, quantitative image velocimetry has considerably grown in popularity in the fluid mechanics research community. More recently, image-based techniques have been extended to hydraulic applications for mapping and quantifying free-surface velocities spanning large areas in free-surface laboratory and natural-scale flows. During the adaptation process it has been proven the great potential that image velocimetry holds for qualitative and quantitative observations hydraulic applications. Current efforts are directed toward evaluating the technique performance, perfecting implementation aspects, and expanding its flow diagnostic capabilities. Presented here are new laboratory measurements that estimate the accuracy of image velocimetry by comparison with alternative instruments, recent developments targeting enhancement of several technique components, and proof-of-concept experiments that demonstrate new measurement and operational capabilities. The ultimate goals of the new experimental evidence are to demonstrate that image velocimetry possesses full-grown capabilities for laboratory hydraulic investigations and has the potential to be successfully implemented in important river and coastal engineering applications.     

Automated Sediment Erosion Testing System Using Digital Imaging

Measurement of vertical profiles of the critical shear stress, τc, and the erosion rate, E, from the same undisturbed sediment core is crucial for modeling the resuspension of fine-grained natural sediments. The automated sediment erosion testing system (ASETS) was developed to determine profiles of τc and E with centimeter spatial (vertical) resolution in an undisturbed (Shelby tube) sediment core, whose surface was eroded by steady turbulent flow through a flume. The unique feature of ASETS is that it is a real-time imaging method that accurately determines the position of the core surface during erosion for both calculating the vertical profile of E and controlling a motor-driver system that automatically pushes up the core to maintain its surface flush with the flume bottom. Undisturbed, field cores were tested over a range of flow (average bed shear stress, τb) conditions. The amount of eroded sediment from both optical backscattering measurements and the imaging method were in good agreement, which validated ASETS. Measured vertical profiles of τc and E were similar to those reported in literature. E correlated well with (τb?τc)2, which agrees with previous results in literature.     

Material-Based Construction Site Image Retrieval

The technological advancements in digital imaging, the widespread popularity of digital cameras, and the increasing demand by owners and contractors for detailed and complete site photograph logs have triggered an ever-increasing growth in the rate of construction image data collection, with thousands of images being stored for each project. However, the sheer volume of images and the difficulties in accurately and manually indexing them have generated a pressing need for methods that can index and retrieve images with minimal or no user intervention. This paper reports recent developments from research efforts in the indexing and retrieval of construction site images in architecture, engineering, construction, and facilities management image database systems. The limitations and benefits of the existing methodologies will be presented, as well as an explanation of the reasons for the development of a novel image retrieval approach that not only can recognize construction materials within the image content in order to index images, but also can be compatible with existing retrieval methods, enabling enhanced results.     

Multimodal Image Retrieval from Construction Databases and Model-Based Systems

In the modern and dynamic construction environment it is important to access information in a fast and efficient manner in order to improve the decision making processes for construction managers. This capability is, in most cases, straightforward with today’s technologies for data types with an inherent structure that resides primarily on established database structures like estimating and scheduling software. However, previous research has demonstrated that a significant percentage of construction data is stored in semi-structured or unstructured data formats (text, images, etc.) and that manually locating and identifying such data is a very hard and time-consuming task. This paper focuses on construction site image data and presents a novel image retrieval model that interfaces with established construction data management structures. This model is designed to retrieve images from related objects in project models or construction databases using location, date, and material information (extracted from the image content with pattern recognition techniques).     

Development of a Virtual Reality Structural Analysis System

This paper discusses the development of virtual structural analysis program (VSAP). This is a virtual environment (VE) based structural analysis system developed through a collaborative effort between the School of Architecture + Design and the Department of Computer Science at Virginia Polytechnic Institute and State Univ. (Virginia Tech). The VSAP was developed by linking a visualization routine using the simple VE library and a structural analysis software, the PC-SAP4. Details of the design of four user interfaces for the VSAP are presented. These user interfaces are: the immersive pen and tablet interface, the desktop interface, the portable immersive interface, and the cave automatic VE immersive interface. Usability studies for each interface were conducted. Results of these studies indicated that the users of VSAP were highly satisfied with the experience. In addition, all the developed interfaces were found to be successful for their specific application.