A Component Decomposition Model for 3D Laser Scanning Pavement Data Based on High-Pass Filtering and Sparse Analysis

Gui, Rong; Xu, Xin; Zhang, Dejin; Lin, Hong; Pu, Fangling; He, Li; Cao, Min

doi:10.3390/s18072294

Cited by 32 publications

(13 citation statements)

References 49 publications

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“…There have been several attempts over the years to carry this task out utilizing different datasets. Studies have tried to extract useful features from drone image data [25], LIDAR point cloud data [30], Google street view image data [31], 3D laser profilers [32,33], 3D laser images [34] and normal 2D images [35]. There have also been attempts to utilize convolutional neural networks for the purpose of segmenting pavement images using annotated masks on the images [36].…”

Section: The Use Of Image Segmentation In Pavement Condition Evaluationsmentioning

confidence: 99%

Exploiting Low-Cost 3D Imagery for the Purposes of Detecting and Analyzing Pavement Distresses

2020

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Road pavement conditions have significant impacts on safety, travel times, costs, and environmental effects. It is the responsibility of road agencies to ensure these conditions are kept in an acceptable state. To this end, agencies are tasked with implementing pavement management systems (PMSs) which effectively allocate resources towards maintenance and rehabilitation. These systems, however, require accurate data. Currently, most agencies rely on manual distress surveys and as a result, there is significant research into quick and low-cost pavement distress identification methods. Recent proposals have included the use of structure-from-motion techniques based on datasets from unmanned aerial vehicles (UAVs) and cameras, producing accurate 3D models and associated point clouds. The challenge with these datasets is then identifying and describing distresses. This paper focuses on utilizing images of pavement distresses in the city of Palermo, Italy produced by mobile phone cameras. The work aims at assessing the accuracy of using mobile phones for these surveys and also identifying strategies to segment generated 3D imagery by considering the use of algorithms for 3D Image segmentation to detect shapes from point clouds to enable measurement of physical parameters and severity assessment. Case studies are considered for pavement distresses defined by the measurement of the area affected such as different types of cracking and depressions. The use of mobile phones and the identification of these patterns on the 3D models provide further steps towards low-cost data acquisition and analysis for a PMS.

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Section: The Use Of Image Segmentation In Pavement Condition Evaluationsmentioning

confidence: 99%

Exploiting Low-Cost 3D Imagery for the Purposes of Detecting and Analyzing Pavement Distresses

2020

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“…Laser measurement-based detection methods use special equipment installed on a separate inspection vehicle, such as a laser scanner, to convert the road surface into a three-dimensional (3D) object in a coordinate system [ 19 , 20 , 21 , 22 ]. This approach can directly calculate various indicators for the precise evaluation of the road-surface condition.…”

Section: Introductionmentioning

confidence: 99%

Detection of Road-Surface Anomalies Using a Smartphone Camera and Accelerometer

Lee

Chun

Ryu

2021

Sensors

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Road surfaces should be maintained in excellent condition to ensure the safety of motorists. To this end, there exist various road-surface monitoring systems, each of which is known to have specific advantages and disadvantages. In this study, a smartphone-based dual-acquisition method system capable of acquiring images of road-surface anomalies and measuring the acceleration of the vehicle upon their detection was developed to explore the complementarity benefits of the two different methods. A road test was conducted in which 1896 road-surface images and corresponding three-axis acceleration data were acquired. All images were classified based on the presence and type of anomalies, and histograms of the maximum variations in the acceleration in the gravitational direction were comparatively analyzed. When the types of anomalies were not considered, it was difficult to identify their effects using the histograms. The differences among histograms became evident upon consideration of whether the vehicle wheels passed over the anomalies, and when excluding longitudinal anomalies that caused minor changes in acceleration. Although the image-based monitoring system used in this research provided poor performance on its own, the severity of road-surface anomalies was accurately inferred using the specific range of the maximum variation of acceleration in the gravitational direction.

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“…In the case of less accessible places, where traditional solutions prove to be inefficient, the approach specified in [35] can be employed, where researchers use appropriate software and measuring instrumentation, namely, a laser scanner. These devices are widely used for structure diagnostic examination, as specified in works [36][37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Nondestructive Testing of the Miter Gates Using Various Measurement Methods

Binczyk

Kalitowski

Szulwic

et al. 2020

Sensors

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When any problems related to civil engineering structures appear, identifying the issue through the usage of only one measuring method is difficult. Therefore, comprehensive tests are required to identify the main source. The strains and displacement measurements, as well as modal identification, are widely used in the nondestructive testing of structures. However, measurements are usually carried out at several points and confirm or exclude only one of many potential causes of the problem. The main aim of this paper is to identify the causes of miter gates’ excessive vibration. The research includes displacement measurements using a tachometer and a laser scanner, acceleration measurements connected with modal analysis, and calculations with the finite element method (FEM) model. The numerical model underwent verification regarding test results. Particular attention was paid to evaluate the practical use of a laser scanner for diagnosing miter gates. Unlike classical methods, it measures many points. The analysis eliminated a number of potential causes of excessive vibration and highlighted the field of excessive deformation. The identified anomaly could be associated with bearings’ misalignment after closing the door. This construction part should be subjected to further research using classical methods. The laser scanning has been proven to be a method that can only generally present the deformation of the structure.

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A Component Decomposition Model for 3D Laser Scanning Pavement Data Based on High-Pass Filtering and Sparse Analysis

Cited by 32 publications

References 49 publications

Exploiting Low-Cost 3D Imagery for the Purposes of Detecting and Analyzing Pavement Distresses

Exploiting Low-Cost 3D Imagery for the Purposes of Detecting and Analyzing Pavement Distresses

Detection of Road-Surface Anomalies Using a Smartphone Camera and Accelerometer

Nondestructive Testing of the Miter Gates Using Various Measurement Methods

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