Automated Detection of Exposed Reinforcement in Post-Earthquake Safety and Structural Evaluations

Post-earthquake structural safety evaluations are currently performed manually by a team of certified inspectors and/or structural engineers. This process is time-consuming and costly, keeping owners and occupants from returning to their businesses and homes. Automating these evaluations would enable faster, and potentially more consistent, relief and response processes. In order to do this, the detection of exposed reinforcing steel is of utmost significance. This paper presents a novel method of detecting exposed reinforcement in concrete columns for the purpose of advancing practices of structural and safety evaluation of buildings after earthquakes. Under this method, the binary image of the reinforcing area is first isolated using a state-of-the-art adaptive thresholding technique. Next, the ribbed regions of the reinforcement are detected by way of binary template matching. Finally, vertical and horizontal profiling are applied to the processed image in order to filter out any superfluous pixels and take into consideration the size of reinforcement bars in relation to that of the structural element within which they reside. The final result is the combined binary image disclosing only the regions containing rebar overlaid on top of the original image. The method is tested on a set of images from the January 2010 earthquake in Haiti. Preliminary test results convey that most exposed reinforcement could be properly detected in images of moderately-to-severely damaged concrete columns.

Detection of Construction Workers in Video Frames for Automatic Initialization of Vision Trackers

Vision based tracking can provide the spatial location of construction entities such as equipment, workers, and materials in large scale, congested construction sites. It tracks entities in video streams by inferring their locations based on the entities’ visual features and motion histories. To initiate the process, it is necessary to determine the pixel areas corresponding to the construction entities to be tracked in the following consecutive video frames. In order to fully automate the process, an automated way of initialization is needed. This paper presents the method for construction worker detection which can automatically recognize and localize construction workers in video frames. The method first finds the foreground areas of moving objects using a background subtraction method. Within these foreground areas, construction workers are recognized based on the histogram of oriented gradients (HOG) and histogram of the HSV colors. HOG’s have proved to work effectively for detection of people, and the histogram of HSV colors helps differentiate between pedestrians and construction workers wearing safety vests. Preliminary experiments show that the proposed method has the potential to automate the initialization process of vision based tracking.

Testing of Depth-Encoded Hough Voting for Infrastructure Object Detection

The lack of viable methods to map and label existing infrastructure is one of the engineering grand challenges for the 21st century. For instance, over two thirds of the effort needed to geometrically model even simple infrastructure is spent on manually converting a cloud of points to a 3D model. The result is that few facilities today have a complete record of as-built information and that as-built models are not produced for the vast majority of new construction and retrofit projects. This leads to rework and design changes that can cost up to 10% of the installed costs. Automatically detecting building components could address this challenge. However, existing methods for detecting building components are not view and scale-invariant, or have only been validated in restricted scenarios that require a priori knowledge without considering occlusions. This leads to their constrained applicability in complex civil infrastructure scenes. In this paper, we test a pose-invariant method of labeling existing infrastructure. This method simultaneously detects objects and estimates their poses. It takes advantage of a recent novel formulation for object detection and customizes it to generic civil infrastructure scenes. Our preliminary experiments demonstrate that this method achieves convincing recognition results.

Enhancement of Construction Equipment Detection in Video Frames by Combining with Tracking

Vision-based object detection has been introduced in construction for recognizing and locating construction entities in on-site camera views. It can provide spatial locations of a large number of entities, which is beneficial in large-scale, congested construction sites. However, even a few false detections prevent its practical applications. In resolving this issue, this paper presents a novel hybrid method for locating construction equipment that fuses the function of detection and tracking algorithms. This method detects construction equipment in the video view by taking advantage of entities' motion, shape, and color distribution. Background subtraction, Haar-like features, and eigen-images are used for motion, shape, and color information, respectively. A tracking algorithm steps in the process to make up for the false detections. False detections are identified by catching drastic changes in object size and appearance. The identified false detections are replaced with tracking results. Preliminary experiments show that the combination with tracking has the potential to enhance the detection performance.

Construction Worker Detection in Video Frames for Initializing Vision Trackers

Monitoring the location of resources on large scale, congested, outdoor sites can be performed more efficiently with vision tracking, as this approach does not require any pre-tagging of resources. However, the greatest impediment to the use of vision tracking in this case is the lack of detection methods that are needed to automatically mark the resources of interest and initiate the tracking. This paper presents such a novel method for construction worker detection that localizes construction workers in video frames. The proposed method exploits motion, shape, and color cues to narrow down the detection regions to moving objects, people, and finally construction workers, respectively. The three cues are characterized by using background subtraction, the histogram of oriented gradients (HOG), and the HSV color histogram. The method has been tested on videos taken in various environments. The results demonstrate its suitability for automatic initialization of vision trackers.

Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments

The current procedures in post-earthquake safety and structural assessment are performed manually by a skilled triage team of structural engineers/certified inspectors. These procedures, and particularly the physical measurement of the damage properties, are time-consuming and qualitative in nature. This paper proposes a novel method that automatically detects spalled regions on the surface of reinforced concrete columns and measures their properties in image data. Spalling has been accepted as an important indicator of significant damage to structural elements during an earthquake. According to this method, the region of spalling is first isolated by way of a local entropy-based thresholding algorithm. Following this, the exposure of longitudinal reinforcement (depth of spalling into the column) and length of spalling along the column are measured using a novel global adaptive thresholding algorithm in conjunction with image processing methods in template matching and morphological operations. The method was tested on a database of damaged RC column images collected after the 2010 Haiti earthquake, and comparison of the results with manual measurements indicate the validity of the method.

ChESS - Quick and Robust Detection of Chess-board Features

Localization of chess-board vertices is a common task in computer vision, underpinning many applications, but relatively little work focusses on designing a specific feature detector that is fast, accurate and robust. In this paper the `Chess-board Extraction by Subtraction and Summation' (ChESS) feature detector, designed to exclusively respond to chess-board vertices, is presented. The method proposed is robust against noise, poor lighting and poor contrast, requires no prior knowledge of the extent of the chess-board pattern, is computationally very efficient, and provides a strength measure of detected features. Such a detector has significant application both in the key field of camera calibration, as well as in Structured Light 3D reconstruction. Evidence is presented showing its robustness, accuracy, and efficiency in comparison to other commonly used detectors both under simulation and in experimental 3D reconstruction of flat plate and cylindrical objects

SOI CMOS integrated zinc oxide nanowire for toluene detection

The paper reports on the in-situ growth of zinc oxide nanowires (ZnONWs) on a complementary metal oxide semiconductor (CMOS) substrate, and their performance as a sensing element for ppm (parts per million) levels of toluene vapour in 3000 ppm humid air. Zinc oxide NWs were grown using a low temperature (only 90°C) hydrothermal method. The ZnONWs were first characterised both electrically and through scanning electron microscopy. Then the response of the on-chip ZnONWs to different concentrations of toluene (400-2600ppm) was observed in air at 300°C. Finally, their gas sensitivity was determined and found to lie between 0.1% and 0.3% per ppm. © 2013 IEEE.

Unconstrained monocular 3D human pose estimation by action detection and cross-modality regression forest

This work addresses the challenging problem of unconstrained 3D human pose estimation (HPE) from a novel perspective. Existing approaches struggle to operate in realistic applications, mainly due to their scene-dependent priors, such as background segmentation and multi-camera network, which restrict their use in unconstrained environments. We therfore present a framework which applies action detection and 2D pose estimation techniques to infer 3D poses in an unconstrained video. Action detection offers spatiotemporal priors to 3D human pose estimation by both recognising and localising actions in space-time. Instead of holistic features, e.g. silhouettes, we leverage the flexibility of deformable part model to detect 2D body parts as a feature to estimate 3D poses. A new unconstrained pose dataset has been collected to justify the feasibility of our method, which demonstrated promising results, significantly outperforming the relevant state-of-the-arts. © 2013 IEEE.

ChESS - Quick and robust detection of chess-board features

Localization of chess-board vertices is a common task in computer vision, underpinning many applications, but relatively little work focusses on designing a specific feature detector that is fast, accurate and robust. In this paper the 'Chess-board Extraction by Subtraction and Summation' (ChESS) feature detector, designed to exclusively respond to chess-board vertices, is presented. The method proposed is robust against noise, poor lighting and poor contrast, requires no prior knowledge of the extent of the chess-board pattern, is computationally very efficient, and provides a strength measure of detected features. Such a detector has significant application both in the key field of camera calibration, as well as in structured light 3D reconstruction. Evidence is presented showing its superior robustness, accuracy, and efficiency in comparison to other commonly used detectors, including Harris & Stephens and SUSAN, both under simulation and in experimental 3D reconstruction of flat plate and cylindrical objects. © 2013 Elsevier Inc. All rights reserved.

Detection of microcystins in environmental samples using surface plasmon resonance biosensor

An indirect inhibitive surface plasmon resonance (SPR) immunoassay was developed for the microcystins (MCs) detection. The bioconjugate of MC-LR and bovine serum albumin (BSA) was immobilized on a CM5 sensor chip. A serial premixture of MC-LR standards (or samples) and monoclonal antibody (mAb) were injected over the functional sensor surface, and the subsequent specific immunoreaction was monitored on the BIAcore 3000 biosensor and generated a signal with an increasing intensity in response to the decreasing MCs concentration. The developed SPR immunoassay has a wide quantitative range in 1-100 mu g L-1. Although not as sensitive as conventional enzyme-linked immunosorbent assay (ELISA), the SPR biosensor offered unique advantages: (I) the sensor chip could be reusable without any significant loss in its binding activity after 50 assay-regeneration cycles, (2) one single assay could be accomplished in 50 min (including 30-min preincubation and 20-min BIAcore analysis), and (3) this method did not require multiple steps. The SPR biosensor was also used to detect MCs in environmental samples, and the results compared well with those obtained by ELISA. We conclude that the SPR biosensor offers outstanding advantages for the MCs detection and may be further developed as a field-portable sensor for real-time monitoring of MCs on site in the near future. (C) 2009 Published by Elsevier B.V.

A high throughput Nile red method for quantitative measurement of neutral lipids in microalgae

Isolation of high neutral lipid-containing microalgae is key to the commercial success of microalgae-based biofuel production. The Nile red fluorescence method has been successfully applied to the determination of lipids in certain microalgae, but has been unsuccessful in many others, particularly those with thick, rigid cell walls that prevent the penetration of the fluorescence dye. The conventional "one sample at a time" method was also time-consuming. In this study, the solvent dimethyl sulfoxide (DMSO) was introduced to microalgal samples as the stain carrier at an elevated temperature. The cellular neutral lipids were determined and quantified using a 96-well plate on a fluorescence spectrophotometer with an excitation wavelength of 530 nm and an emission wavelength of 575 run. An optimized procedure yielded a high correlation coefficient (R-2 = 0.998) with the lipid standard triolein and repeated measurements of replicates. Application of the improved method to several green algal strains gave very reproducible results with relative standard errors of 8.5%, 3.9% and 8.6%, 4.5% for repeatability and reproducibility at two concentration levels (2.0 mu g/mL and 20 mu g/mL), respectively. Moreover, the detection and quantification limits of the improved Nile red staining method were 0.8 mu g/mL and 2.0 mu g/mL for the neutral lipid standard triolein, respectively. The modified method and a conventional gravimetric determination method provided similar results on replicate samples. The 96-well plate-based Nile red method can be used as a high throughput technique for rapid screening of a broader spectrum of naturally-occurring and genetically-modified algal strains and mutants for high neutral lipid/oil production. (C) 2009 Published by Elsevier B.V.

Detection of serum and mucosal antibody production and antibody secreting cells (ASCs) in large yellow croaker (Pseudosciaena crocea) following vaccination with Vibrio harveyi via different routes

The kinetics of mucosal and serum antibody response is well as antibody secreting cells (ASCs) production were studied in large yellow croaker following vaccination with inactivated Vibrio harveyi by different routes: oral administration. intraperitoneal (IP) injection and immersion. Indirect ELISA was used to measure the antibody level in serum and cutaneous mucus, and ELISPOT was used to monitor the ASCs derived from gill, blood and head kidney. The data demonstrated that IP injection resulted in the highest antibody levels in the systemic circulation, whereas immersion induced significant antibody levels in mucous. As for the ASCs response, IP injection induced high numbers of ASCs in the head kidney and blood; oral intubation only induced a slight ASCs response in the head kidney: immersion induced a much stronger ASCs response in the gill. These results indicate that mucosal antibodies following immersion immunization are independent of a systemic response and more sensitive, since it could be triggered earlier than serum antibodies. The mucosal antibodies following IP injection immunization may depend oil a systemic immune response. The protective effects of the three vaccination methods were compared by challenging with live V. harveyi. Survival of the three groups of vaccinated fish varied front 40 to 60%. while 100% mortality was found in control fish. Compared with IP and oral vaccination, immersion stimulated higher specific antibody titers in the mucosal system and achieved similar protection, so it is in effective and efficient method for immunizing a large number of fish against V harveyi (C) 2008 Elsevier B.V. All rights reserved.

Detection of the hepatotoxic microcystins in 36 kinds of cyanobacteria Spirulina food products in China

Gel filtration chromatography, ultra-filtration, and solid-phase extraction silica gel clean-up were evaluated for their ability to remove microcystins selectively from extracts of cyanobacteria Spirulina samples after using the reversed-phase octadecylsilyl ODS cartridge for subsequent analysis by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). The reversed-phase ODS cartridge/silica gel combination were effective and the optimal wash and elution conditions were: H2O (wash), 20% methanol in water (wash), and 90% methanol in water (elution) for the reversed-phase ODS cartridge, followed by 80% methanol in water elution in the silica gel cartridge. The presence of microcystins in 36 kinds of cyanobacteria Spirulina health food samples obtained from various retail outlets in China were detected by LC-MS/MS, and 34 samples (94%) contained microcystins ranging from 2 to 163 ng g(-1) (mean=1427 ng g(-1)), which were significantly lower than microcystins present in blue green alga products previously reported. MC-RR-which contains two molecules of arginine (R)-(in 94.4% samples) was the predominant microcystin, followed by MC-LR-where L is leucine-(30.6%) and MC-YR-where Y is tyrose-(27.8%). The possible potential health risks from chronic exposure to microcystins from contaminated cyanobacteria Spirulina health food should not be ignored, even if the toxin concentrations were low. The method presented herein is proposed to detect microcystins present in commercial cyanobacteria Spirulina samples.

A novel chemiluminescent immunoassay for microcystin (MC) detection based on gold nanoparticles label and its application to MC analysis in aquatic environmental samples

A novel chemiluminescent immunoassay method based on gold nanoparticles was developed for the detection of microcystins (MCs). The immunoassay included three main steps: indirect competitive immunoreaction, oxidative dissolution of gold nanoparticles, and indirect determination for MCs with Au3+-catalysed luminol chemiluminesent system. The method has a wide working range (0.05-10 mu g L-1, r(2) = 0.9914), the limit of detection was determined to be 0.024 mu g L-1, which is much lower than the World Health Organization's proposed guidelines (1 mu g L-1) for drinking-water. The proposed method was applied to MC analysis in natural water and fish tissue samples, and most results in the proposed method were in agreement with the conventional indirect competitive enzyme-linked immunosorbent assay method, which indicated that the new chemiluminescent immunoassay was sensitive, reliable, and suitable for MC analysis in natural water and fish tissue samples.