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Advances in 3D Sensing Techniques and Its Applications
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Advances in 3D Sensing Techniques and Its Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: closed (20 November 2024) | Viewed by 12224

Special Issue Editor

Dr. Dongliang Zheng

E-Mail Website
Guest Editor
School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Interests: optical measurement; 3D reconstruction; pattern recognition; machine vision

Special Issue Information

Dear Colleagues,

Three-dimensional (3D) sensing plays an important role in advanced manufacturing, reverse engineering, virtual reality, etc. We would like to invite you to submit original research papers for the related topics, which are detailed below. In addition, research papers which discuss novel optical 3D sensing methods, measurement systems and applications of computer vision are also welcome. This Special Issue focuses on the 3D measurement of shapes and deformations using optical methods and its applications.

In this Special Issue, original research articles and reviews are welcome. The research areas may include, but are not limited to:

  • Three-dimensional shape and deformation measurement;
  • High-speed and dynamic 3D measurement;
  • Computer vision;
  • Fringe projection profilometry;
  • Digital image correlation (DIC);
  • Interferometry;
  • Optical method;
  • Fringe analysis;
  • Phase retrieval;
  • Image processing.

I look forward to receiving your contributions.

Dr. Dongliang Zheng
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (7 papers)

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Research

29 pages, 18651 KiB  
Article
Realization of Impression Evidence with Reverse Engineering and Additive Manufacturing
by Osama Abdelaal and Saleh Ahmed Aldahash
Appl. Sci. 2024, 14(13), 5444; https://doi.org/10.3390/app14135444 - 23 Jun 2024
Viewed by 1181
Abstract
Significant advances in reverse engineering and additive manufacturing have the potential to provide a faster, accurate, and cost-effective process chain for preserving, analyzing, and presenting forensic impression evidence in both 3D digital and physical forms. The objective of the present research was to [...] Read more.
Significant advances in reverse engineering and additive manufacturing have the potential to provide a faster, accurate, and cost-effective process chain for preserving, analyzing, and presenting forensic impression evidence in both 3D digital and physical forms. The objective of the present research was to evaluate the capabilities and limitations of five 3D scanning technologies, including laser scanning (LS), structured-light (SL) scanning, smartphone (SP) photogrammetry, Microsoft Kinect v2 RGB-D camera, and iPhone’s LiDAR (iLiDAR) Sensor, for 3D reconstruction of 3D impression evidence. Furthermore, methodologies for 3D reconstruction of latent impression and visible 2D impression based on a single 2D photo were proposed. Additionally, the FDM additive manufacturing process was employed to build impression evidence models created by each procedure. The results showed that the SL scanning system generated the highest reconstruction accuracy. Consequently, the SL system was employed as a benchmark to assess the reconstruction quality of other systems. In comparison to the SL data, LS showed the smallest absolute geometrical deviations (0.37 mm), followed by SP photogrammetry (0.78 mm). In contrast, the iLiDAR exhibited the largest absolute deviations (2.481 mm), followed by Kinect v2 (2.382 mm). Additionally, 3D printed impression replicas demonstrated superior detail compared to Plaster of Paris (POP) casts. The feasibility of reconstructing 2D impressions into 3D models is progressively increasing. Finally, this article explores potential future research directions in this field. Full article
(This article belongs to the Special Issue Advances in 3D Sensing Techniques and Its Applications)
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15 pages, 4272 KiB  
Article
Precise Cadastral Survey of Rural Buildings Based on Wall Segment Topology Analysis from Dense Point Clouds
by Bo Xu, Zhaochen Han and Min Chen
Appl. Sci. 2023, 13(18), 10197; https://doi.org/10.3390/app131810197 - 11 Sep 2023
Viewed by 1165
Abstract
The renewal and updating of the cadastre of real estate is a long and tedious task for land administration, especially for rural buildings that lack unified design and planning. In order to retain the required accuracy of all points in the register, huge [...] Read more.
The renewal and updating of the cadastre of real estate is a long and tedious task for land administration, especially for rural buildings that lack unified design and planning. In order to retain the required accuracy of all points in the register, huge extensive manual editing is often required. In this work, a precise cadastral survey approach is proposed using Unmanned Aerial Vehicle (UAV) imagery-based stereo point clouds. To ensure the accuracy and uniqueness of building outer walls, the non-maximum suppression of wall points that can separate noise and avoid repeated extraction is proposed. Meanwhile, the multiple cue weighted RANSAC, considering both point-to-line distance and normal consistency, is proposed to reduce the influence of building attachments and avoid spurious edges. For a better description of wall topology, the wall line segment topology graph (WLTG), which can guide the connection of adjacent lines and support the searching of closed boundaries through the minimum graph loop analysis, is also built. Experimental results show that the proposed method can effectively detect the building vector contours with high precision and correct topology, and the detection completeness and correctness of the edge corners can reach 84.9% and 93.2% when the mean square error is below 10 cm. Full article
(This article belongs to the Special Issue Advances in 3D Sensing Techniques and Its Applications)
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18 pages, 8820 KiB  
Article
Soft Segmentation of Terrestrial Laser Scanning Point Cloud of Forests
by Mingrui Dai and Guohua Li
Appl. Sci. 2023, 13(10), 6228; https://doi.org/10.3390/app13106228 - 19 May 2023
Cited by 5 | Viewed by 1261
Abstract
As the three-dimensional (3D) laser scanner is widely used for forest inventory, analyzing and processing point cloud data captured with a 3D laser scanner have become an important research topic in recent years. The extraction of single trees from point cloud data is [...] Read more.
As the three-dimensional (3D) laser scanner is widely used for forest inventory, analyzing and processing point cloud data captured with a 3D laser scanner have become an important research topic in recent years. The extraction of single trees from point cloud data is essential for further investigation at the individual tree level, such as counting trees and trunk analysis, and many developments related to this topic have been published. However, constructing an accurate and automated method to obtain the tree crown silhouette from the point cloud data is challenging because the tree crowns often overlap between adjacent trees. A soft segmentation method that uses K-Nearest Neighbor (KNN) and contour shape constraints at the overlap region is proposed to solve this task. Experimental results show that the visual effect of the tree crown shape and the precision of point cloud segmentation have improved. It is concluded that the proposed method works well for tree crown segmentation and silhouette reconstruction from the terrestrial laser scanning point cloud data of the forest. Full article
(This article belongs to the Special Issue Advances in 3D Sensing Techniques and Its Applications)
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21 pages, 11494 KiB  
Article
A 3D Occlusion Facial Recognition Network Based on a Multi-Feature Combination Threshold
by Kaifeng Zhu, Xin He, Zhuang Lv, Xin Zhang, Ruidong Hao, Xu He, Jun Wang, Jiawei He, Lei Zhang and Zhiya Mu
Appl. Sci. 2023, 13(10), 5950; https://doi.org/10.3390/app13105950 - 11 May 2023
Viewed by 1989
Abstract
In this work, we propose a 3D occlusion facial recognition network based on a multi-feature combination threshold (MFCT-3DOFRNet). First, we design and extract the depth information of the 3D face point cloud, the elevation, and the azimuth angle of the normal vector as [...] Read more.
In this work, we propose a 3D occlusion facial recognition network based on a multi-feature combination threshold (MFCT-3DOFRNet). First, we design and extract the depth information of the 3D face point cloud, the elevation, and the azimuth angle of the normal vector as new 3D facially distinctive features, so as to improve the differentiation between 3D faces. Next, we propose a multi-feature combinatorial threshold that will be embedded at the input of the backbone network to implement the removal of occlusion features in each channel image. To enhance the feature extraction capability of the neural network for missing faces, we also introduce a missing face data generation method that enhances the training samples of the network. Finally, we use a Focal-ArcFace loss function to increase the inter-class decision boundaries and improve network performance during the training process. The experimental results show that the method has excellent recognition performance for unoccluded faces and also effectively improves the performance of 3D occlusion face recognition. The average Top-1 recognition rate of the proposed MFCT-3DOFRNet for the Bosphorus database is 99.52%, including 98.94% for occluded faces and 100% for unoccluded faces. For the UMB-DB dataset, the average Top-1 recognition rate is 95.08%, including 93.41% for occluded faces and 100% for unoccluded faces. These 3D face recognition experiments show that the proposed method essentially meets the requirements of high accuracy and good robustness. Full article
(This article belongs to the Special Issue Advances in 3D Sensing Techniques and Its Applications)
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12 pages, 2082 KiB  
Article
Multi-Frequency Fringe Projection Profilometry: Phase Error Suppression Based on Cycle Count Adjustment
by Zuqi Ma, Zongsheng Lu, Yongling Li and Yuntong Dai
Appl. Sci. 2023, 13(8), 5117; https://doi.org/10.3390/app13085117 - 20 Apr 2023
Cited by 2 | Viewed by 1913
Abstract
Fringe projection profilometry is one of the most widely used three-dimensional measurement techniques at present, in which phase is the key factor for the accuracy of dimensional measurements. Jumping errors may occur due to improper handling of truncation points in phase unwrapping. Meanwhile, [...] Read more.
Fringe projection profilometry is one of the most widely used three-dimensional measurement techniques at present, in which phase is the key factor for the accuracy of dimensional measurements. Jumping errors may occur due to improper handling of truncation points in phase unwrapping. Meanwhile, projective dual-frequency grating has the shortcomings of a narrow measurement range and coarse projection fringe due to the requirements of an overlapping grid. To address the above problems, this paper puts forward an improved multi-frequency heterodyne phase unwrapping approach. Firstly, the phase principal values of three frequencies are obtained by the standard four-step phase-shifting approach, and two wrapped phases with lower frequencies are obtained through the dual-frequency heterodyne phase unwrapping approach. Then, the decimal part of the fringe order is again calculated using the dual-frequency heterodyne principle, and the actual value of the current decimal part is calculated from the phase principal values of the grating fringe corresponding to the fringe order. Then, a threshold is set according to the error of the phase principal value itself, and the differences between this threshold and the above calculated and theoretical values are compared. Finally, the absolute phase is corrected by adjusting the number of cycles according to the judgment results. Experiments show that the improved approach can achieve a correction rate of more than 96.8% for the jumping errors that occur in phase unwrapping, and it is also highly resistant to noise in the face of different noises. Furthermore, the approach can measure the three-dimensional morphology of objects with different surface morphologies, indicating the certain universality of the approach. Full article
(This article belongs to the Special Issue Advances in 3D Sensing Techniques and Its Applications)
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12 pages, 2378 KiB  
Article
Mueller Matrix Decomposition and Image for Non-Destructive Testing of UAVs Skin
by Hongzhe Li, Lin Li, Xiaolei Yu, Delong Meng, Ciyong Gu, Zhenlu Liu and Zhimin Zhao
Appl. Sci. 2023, 13(4), 2609; https://doi.org/10.3390/app13042609 - 17 Feb 2023
Cited by 1 | Viewed by 1491
Abstract
Recently, Mueller matrix polarimetry (MMP) has been widely applied in many aspects, such as radar target decomposition, monitoring the glucose level, tissue diagnostics, biological samples, etc., but it is still challenging for the complex light–matter interactions of rough surfaces and non-uniform structures such [...] Read more.
Recently, Mueller matrix polarimetry (MMP) has been widely applied in many aspects, such as radar target decomposition, monitoring the glucose level, tissue diagnostics, biological samples, etc., but it is still challenging for the complex light–matter interactions of rough surfaces and non-uniform structures such as 3D composite materials. In this work, a unitary matrix-based Mueller matrix decomposition (UMMMD) is proposed for non-destructive testing (NDT) of unmanned aerial vehicles (UAVs) skin. The decomposition model is constructed by the unitary matrix transformation of coherency matrices. In the model, the non-uniform depolarization caused by multiple scattering is quantified with the depolarization matrix and the entropy. From this model, the Mueller matrix of multiple scattering media can be completely decomposed. The proposed method can provide more polarization information than some traditional methods for multiple scattering under different polarization states. The contrast of the obtained polarization image can be improved by about 13 times compared to that of the original image. In addition, the key features of UAV skin such as deformation, shear angles, and density are obtained. The shear angles vary from 17° to 90°, and the average density is about 20/cm2. The provided experimental results show that this method is effective for the NDT of UAVs skin. The method also shows great potential for applications in target decomposition, NDT of 3D composite materials, 3D polarization imaging, light–matter interactions of non-uniform complex structures, etc. Full article
(This article belongs to the Special Issue Advances in 3D Sensing Techniques and Its Applications)
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14 pages, 9881 KiB  
Article
Research on Morphology Detection of Metal Additive Manufacturing Process Based on Fringe Projection and Binocular Vision
by Min Wang, Qican Zhang, Qian Li, Zhoujie Wu, Chaowen Chen, Jin Xu and Junpeng Xue
Appl. Sci. 2022, 12(18), 9232; https://doi.org/10.3390/app12189232 - 14 Sep 2022
Cited by 7 | Viewed by 2224
Abstract
This paper considers the three-dimensional (3D) shape measurement of metal parts during an additive manufacturing process in a direct energy deposition (DED) printing system with high temperature and strong light; a binocular measurement system based on ultraviolet light source projection is built using [...] Read more.
This paper considers the three-dimensional (3D) shape measurement of metal parts during an additive manufacturing process in a direct energy deposition (DED) printing system with high temperature and strong light; a binocular measurement system based on ultraviolet light source projection is built using fringe projection and Fourier analysis. Firstly, ultraviolet light projection and an optical filter are used to obtain high-quality fringe patterns in an environment with thermal radiation. Then, Fourier analysis is carried out by using a single deformed fringe, and a spatial phase unwrapping algorithm is applied to obtain an unambiguous unwrapping phase, which is used as the guiding basis for the binocular matching process and 3D shape reconstruction. Finally, the accuracy of the measuring system is evaluated using a standard ball-bar gauge and the measurement error of this system is within 0.05 mm @ 100 × 100 mm. The results show that the system can measure 3D shape changes of metal parts in the additive manufacturing process. The proposed method and system have the potential to be used for online inspection and quality control of additive manufacturing. Full article
(This article belongs to the Special Issue Advances in 3D Sensing Techniques and Its Applications)
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