Recognition of Planar Segments in Point Cloud based on Wavelet Transform

Jakovljević, Živana; Puzović, Radovan; Pajić, Miroslav

doi:10.1109/tii.2015.2389195

Cited by 24 publications

(17 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wavelet analysis is used in many geometric problem solutions and point cloud processing, for example, in [29,43]. Wavelet transform represents a one-dimensional signal f (t) as a linear superposition of atomic functions called wavelets.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Improvement of 3D Power Line Extraction from Multiple Low-Cost UAV Imagery Using Wavelet Analysis

Fryśkowska

2019

Sensors

View full text Add to dashboard Cite

Three-dimensional (3D) mapping of power lines is very important for power line inspection. Many remotely-sensed data products like light detection and ranging (LiDAR) have been already studied for power line surveys. More and more data are being obtained via photogrammetric measurements. This increases the need for the implementation of advanced processing techniques. In recent years, there have been several developments in visualisation techniques using UAV (unmanned aerial vehicle) platform photography. The most modern of such imaging systems have the ability to generate dense point clouds. However, image-based point cloud accuracy is very often various (unstable) and dependent on the radiometric quality of images and the efficiency of image processing algorithms. The main factor influencing the point cloud quality is noise. Such problems usually arise with data obtained via low-cost UAV platforms. Therefore, generated point clouds representing power lines are usually incomplete and noisy. To obtain a complete and accurate 3D model of power lines and towers, it is necessary to develop improved data processing algorithms. The experiment tested the algorithms on power lines with different voltages. This paper presents the wavelet-based method of processing data acquired with a low-cost UAV camera. The proposed, original method involves the application of algorithms for coarse filtration and precise filtering. In addition, a new way of calculating the recommended flight height was proposed. At the end, the accuracy assessment of this two-stage filtration process was examined. For this, point quality indices were proposed. The experimental results show that the proposed algorithm improves the quality of low-cost point clouds. The proposed methods improve the accuracy of determining the parameters of the lines by more than twice. About 10% of noise is reduced by using the wavelet-based approach.

show abstract

Section: Methodsmentioning

confidence: 99%

“…There are only a few methods which allow the level of decomposition to be defined for signals, and often, it is a theoretical or empirical estimation. The main way to define it is by means of entropy [43].…”

Section: Methodsmentioning

confidence: 99%

Improvement of 3D Power Line Extraction from Multiple Low-Cost UAV Imagery Using Wavelet Analysis

Fryśkowska

2019

Sensors

View full text Add to dashboard Cite

show abstract

“…Spectral methods are also introduced in point cloud clustering. As a practical and precise tool , wavelet transform [35]- [37] was introduced to specify and preserve surface features. Pauly et al [38] introduced discrete Fourier transform into surface clustering, noise removal, enhancement, restoration and subsampling.…”

Section: Fig1 Application Framework Of Automatic Assembly Line Basedmentioning

confidence: 99%

Fast Assembly Tolerance Inspection Method Using Feature-Based Adaptive Scale Reduction in Automatic Assembly Line

Qiu

Zhang

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Enormous computation and long data processing time of the online tolerance inspection procedure has been a bottleneck in reducing the production cycle time of automatic assembly line. To reduce time consumption while maintaining accuracy, a fast assembly tolerance inspection method is proposed in this paper using scale-reduced models. First, the general part surface, input by a laser-scanned dense point cloud, is segmented through feature-based clustering. Shape variation estimation are designed to determine reduction ratios between clusters adaptively. Then, assembly simulation method is further advanced to utilize coarse point models with imbalanced density. Finally, numerical experiments are designed to estimate both static and dynamic assembly tolerances as results of tolerance inspection. A case study on a motion component of a rail material transporter shows that the proposed method could reduce 81% of the data processing time compared to traditional practice. The precision loss has minor influence on the inspection results because spatial positioning error is no more than 6% of tolerance interval and 18% of scanning resolution. Moreover, the proposed method has a comprehensive advantage of time and accuracy than two conventional point cloud simplification techniques based on iterative and clustering methods.

show abstract

“…Setting up "Datasocketservermanager": the monitoring terminals IPI (10.13.81.188) and IPZ (10.13.81.181) are added in defaultreaders and defaultwriters so that the monitoring terminals can read and write in the server-side data storage area [14].…”

Section: Implementation Of System Serversmentioning

confidence: 99%

Construction of a Power Quality Monitoring System Based on the Wavelet Transform Change-Point Detection Algorithm on the Virtual Instrument Platform

Shi

Wang

2020

International Journal of Circuits, Systems and Signal Processing

View full text Add to dashboard Cite

It is aimed to carry out the investigation on power quality detection, promote the realization of efficient transmission of network data, and expand the application of wavelet transform change-point detection algorithm in the monitoring system. The voltage deviation is used as a starting point to explore the detection of power quality. First, it describes the harmonics of the public power grid and the limits of harmonic voltage. Second, based on the virtual instrument platform, the power quality monitoring system based on wavelet transform change-point detection algorithm is completed. Finally, by adding a monitoring terminal and a service terminal, the design of the monitoring system server is completed. Through the analysis of the experimental results, it is found that in the monitoring system, the current waveform and the three-phase voltage can be accurately displayed. The combined design of the networked monitoring system and the system server enables the system to complete the rapid transmission of data related to power quality, while having a good monitoring effect. For the optimization of networked monitoring experienceof the server, the application of wavelet transform in power quality measurement is realized. The power quality monitoring system proposed has a strong practicality in power quality monitoring.

show abstract

Recognition of Planar Segments in Point Cloud based on Wavelet Transform

Cited by 24 publications

References 46 publications

Improvement of 3D Power Line Extraction from Multiple Low-Cost UAV Imagery Using Wavelet Analysis

Improvement of 3D Power Line Extraction from Multiple Low-Cost UAV Imagery Using Wavelet Analysis

Fast Assembly Tolerance Inspection Method Using Feature-Based Adaptive Scale Reduction in Automatic Assembly Line

Construction of a Power Quality Monitoring System Based on the Wavelet Transform Change-Point Detection Algorithm on the Virtual Instrument Platform

Contact Info

Product

Resources

About