Three-dimensional Information Research Articles

Insulator Extraction from UAV LiDAR Point Cloud Based on Multi-Type and Multi-Scale Feature Histogram

Insulators are key components to ensure the normal operation of power facilities in transmission corridors. Existing insulator identification methods mainly use image data and lack the acquisition of three-dimensional information. This paper proposes an efficient insulator extraction method based on UAV (unmanned aerial vehicle) LiDAR (light detection and ranging) point cloud, using five histogram features: horizontal density (HD), horizontal void (HV), horizontal width (HW), vertical width (VW) and vertical void (VV). Firstly, a voxel-based method is employed to roughly extract power lines and pylons from the original point cloud. Secondly, the VV histogram is used to categorize the pylons into suspension and tension types, and the HD histogram is used to locate the tower crossarm and further refine the roughly extracted powerlines. Then, for the suspension tower, insulators are segmented based on the HV histogram and HD difference histogram. For the tension tower, the HW histogram is used to recognize the jumper conductor (JC) and transmission conductor (TC) from the power line. The HW histogram and VW histogram are used to extract the tension insulator in the TC and suspension insulator in the JC, respectively. Finally, considering the problem of setting a suitable grid width when constructing the feature histogram, an adaptive method of multi-scale histograms is proposed to refine the extraction result. Two 220 kV long transmission lines are used for the validation, and the overall object-based accuracy for suspension and tension towers are 100% and 97.3%, respectively. Compared with the point feature-based method, the mean F1 score of the proposed method improved by 0.3, and the runtime for each tower is within 2 s.

Quantum dot-enabled infrared hyperspectral imaging with single-pixel detection.

Near-infrared (NIR) hyperspectral imaging is a powerful technique that enables the capture of three-dimensional (3D) spectra-spatial information within the NIR spectral range, offering a wide array of applications. However, the high cost associated with InGaAs focal plane array (FPA) has impeded the widespread adoption of NIR hyperspectral imaging. Addressing this challenge, in this study, we adopt an alternative approach-single-pixel detection for NIR hyperspectral imaging. Our investigation reveals that single-pixel detection outperforms conventional FPA, delivering a superior signal-to-noise ratio (SNR) for both spectral and imaging reconstruction. To implement this strategy, we leverage self-assembled colloidal quantum dots (CQDs) and a digital micromirror device (DMD) for NIR spectral and spatial information multiplexing, complemented by single-pixel detection for simultaneous spectral and image reconstruction. Our experimental results demonstrate successful NIR hyperspectral imaging with a detection window about 600 nm and an average spectral resolution of 8.6 nm with a pixel resolution of 128 × 128. The resulting spectral and spatial data align well with reference instruments, which validates the effectiveness of our approach. By circumventing the need for expensive and bulky FPA and wavelength selection components, our solution shows promise in advancing affordable and accessible NIR hyperspectral imaging technologies, thereby expanding the range of potential applications.

Parameter Extraction of Accelerated Moving Targets under Non-Quasi-Axial Incidence Conditions Based on Vortex Electromagnetic Wave Radar

Vortex electromagnetic wave radar carrying orbital angular momentum can compensate for the deficiency of planar electromagnetic wave radar in detecting motion parameters perpendicular to the direction of electromagnetic wave propagation, thus providing more information for target recognition, which has become a hot research field in recent years. However, existing research makes it difficult to obtain the acceleration and rotation centers of targets under non-quasi-axial incidence conditions of vortex electromagnetic waves. Based on this, this article proposes a variable speed motion target parameter extraction method that combines single element and total element echoes. This method can achieve three-dimensional information extraction of radar targets based on a uniform circular array (UCA). Firstly, we establish a non-quasi-axis detection echo model for variable-speed moving targets and extract echoes from different array elements. Then, a single element echo is used to extract the target’s range slow time profile and obtain the target’s rotation center z coordinate. We further utilize the target linear, angular Doppler frequency shift extremum, and median information to extract parameters such as target acceleration, tilt angle, rotation radius, and rotation center x and y coordinates. We analyzed the impact of different signal-to-noise ratios and motion states on parameter extraction. The simulation results have verified the effectiveness of the proposed algorithm.

Internal magnetic field structures observed by PSP/WISPR in a filament-related coronal mass ejection

We investigated the coronal mass ejection (CME) related to an eruptive filament over the southwestern solar limb on December 8, 2022, at around 8 UT. We tracked localized density enhancements reflecting the magnetic structures using white-light data taken with the Wide-field Instrument for Solar PRobe (WISPR) aboard the Parker Solar Probe (PSP). We aim to investigate the 3D location, morphology and evolution of the internal magnetic fine structures of CMEs. Specifically, we focused on the physical origin of the features in the WISPR images, how the white-light structures evolve over time, and their relationship with the source region, filament, and the flux rope. The fast tangential motion of the PSP spacecraft during its perihelion permits a single event to be viewed from multiple angles in short times relative to the event's evolution. Hence, three-dimensional information of selected CME features can be derived from this single spacecraft using triangulation techniques. We grouped small-scale structures with roughly similar speeds, longitude, and latitude into three distinct morphological groups. We found twisted magnetic field patterns close to the eastern leg of the CME that may be related to "horns" outlining the edges of the flux-rope cavity. We identified aligned thread-like bundles close to the western leg, and they may be related to confined density enhancements evolving during the filament eruption. High density blob-like features (magnetic islands) are widely spread in longitude (sim 40°) close to the flanks and the rear part of the CME. We also note that the large-scale outer envelope of the CME, seen clearly from 1 AU, was not well observed by PSP. We demonstrate that CME flux ropes, apart from the blobs, may comprise different morphological groups with a cluster behavior; the blobs instead span a wide range of longitudes. This finding may hint at either the three-dimensionality of the post-CME current sheet (CS) or the influence of the ambient corona in the evolutionary behavior of the CS. Importantly, we show that the global appearance of the CME can be very different in WISPR (0.11--0.16 AU) and the instruments near 1 AU because of the shorter line-of-sight integration of WISPR.

Organ Segmentation and Phenotypic Trait Extraction of Cotton Seedling Point Clouds Based on a 3D Lightweight Network

Cotton is an important economic crop; therefore, enhancing cotton yield and cultivating superior varieties are key research priorities. The seedling stage, a critical phase in cotton production, significantly influences the subsequent growth and yield of the crop. Therefore, breeding experts often choose to measure phenotypic parameters during this period to make breeding decisions. Traditional methods of phenotypic parameter measurement require manual processes, which are not only tedious and inefficient but can also damage the plants. To effectively, rapidly, and accurately extract three-dimensional phenotypic parameters of cotton seedlings, precise segmentation of phenotypic organs must first be achieved. This paper proposes a neural network-based segmentation algorithm for cotton seedling organs, which, compared to the average precision of 75.4% in traditional unsupervised learning, achieves an average precision of 96.67%, demonstrating excellent segmentation performance. The segmented leaf and stem point clouds are used for the calculation of phenotypic parameters such as stem length, leaf length, leaf width, and leaf area. Comparisons with actual measurements yield coefficients of determination R2 of 91.97%, 90.97%, 92.72%, and 95.44%, respectively. The results indicate that the algorithm proposed in this paper can achieve precise segmentation of stem and leaf organs, and can efficiently and accurately extract three-dimensional phenotypic structural information of cotton seedlings. In summary, this study not only made significant progress in the precise segmentation of cotton seedling organs and the extraction of three-dimensional phenotypic structural information, but the algorithm also demonstrates strong applicability to different varieties of cotton seedlings. This provides new perspectives and methods for plant researchers and breeding experts, contributing to the advancement of the plant phenotypic computation field and bringing new breakthroughs and opportunities to the field of plant science research.

In Silico and In Vitro Evaluation of the Molecular Mimicry of the SARS-CoV-2 Spike Protein by Common Short Constituent Sequences (cSCSs) in the Human Proteome: Toward Safer Epitope Design for Vaccine Development.

Spike protein sequences in SARS-CoV-2 have been employed for vaccine epitopes, but many short constituent sequences (SCSs) in the spike protein are present in the human proteome, suggesting that some anti-spike antibodies induced by infection or vaccination may be autoantibodies against human proteins. To evaluate this possibility of "molecular mimicry" in silico and in vitro, we exhaustively identified common SCSs (cSCSs) found both in spike and human proteins bioinformatically. The commonality of SCSs between the two systems seemed to be coincidental, and only some cSCSs were likely to be relevant to potential self-epitopes based on three-dimensional information. Among three antibodies raised against cSCS-containing spike peptides, only the antibody against EPLDVL showed high affinity for the spike protein and reacted with an EPLDVL-containing peptide from the human unc-80 homolog protein. Western blot analysis revealed that this antibody also reacted with several human proteins expressed mainly in the small intestine, ovary, and stomach. Taken together, these results showed that most cSCSs are likely incapable of inducing autoantibodies but that at least EPLDVL functions as a self-epitope, suggesting a serious possibility of infection-induced or vaccine-induced autoantibodies in humans. High-risk cSCSs, including EPLDVL, should be excluded from vaccine epitopes to prevent potential autoimmune disorders.

Group sparse-based Taylor expansion method for liver pharmacokinetic parameters imaging of dynamic fluorescence molecular tomography

Objective. Pharmacokinetic parametric images obtained through dynamic fluorescence molecular tomography (DFMT) has ability of capturing dynamic changes in fluorescence concentration, thereby providing three-dimensional metabolic information for applications in biological research and drug development. However, data processing of DFMT is time-consuming, involves a vast amount of data, and the problem itself is ill-posed, which significantly limits the application of pharmacokinetic parametric images reconstruction. In this study, group sparse-based Taylor expansion method is proposed to address these problems. Approach. Firstly, Taylor expansion framework is introduced to reduce time and computational cost. Secondly, group sparsity based on structural prior is introduced to improve reconstruction accuracy. Thirdly, alternating iterative solution based on accelerated gradient descent algorithm is introduced to solve the problem. Main results. Numerical simulation and in vivo experimental results demonstrate that, in comparison to existing methods, the proposed approach significantly enhances reconstruction speed without a degradation of quality, particularly when confronted with background fluorescence interference from other organs. Significance. Our research greatly reduces time and computational cost, providing strong support for real-time monitoring of liver metabolism.

Revealing the complexity of meniscus microvasculature through 3D visualization and analysis

Three-dimensional information is essential for a proper understanding of the healing potential of the menisci and their overall role in the knee joint. However, to date, the study of meniscal vascularity has relied primarily on two-dimensional imaging techniques. Here we present a method to elucidate the intricate 3D meniscal vascular network, revealing its spatial arrangement, connectivity and density. A polymerizing contrast agent was injected into the femoral artery of human cadaver legs, and the meniscal microvasculature was examined using micro-computed tomography at different levels of detail and resolution. The 3D vascular network was quantitatively assessed in a zone-base analysis using parameters such as diameter, length, tortuosity, and branching patterns. The results of this study revealed distinct vascular patterns within the meniscus, with the highest vascular volume found in the outer perimeniscal zone. Variations in vascular parameters were found between the different circumferential and radial meniscal zones. Moreover, through state-of-the-art 3D visualization using micro-CT, this study highlighted the importance of spatial resolution in accurately characterizing the vascular network. These findings, both from this study and from future research using this technique, improve our understanding of microvascular distribution, which may lead to improved therapeutic strategies.

Research on Dynamic Updating Technology of Digital Maps for Mobile Communications Based on Multi source Remote Sensing Images

Abstract. With the rapid development of 5G networks in China, mobile communication network simulation technology has gradually become a widely studied direction in the academic and application fields. This study focuses on three-dimensional digital geographic information data for mobile communication, including a large amount of geographic information data that significantly affects the propagation of mobile communication radio waves, such as terrain height and ground use types. These data play a crucial role in coverage prediction, interference analysis, and frequency planning in various telecommunications planning software. This article starts from the perspective of mobile communication network management, and combines typical large-scale terrain data production practice projects for mobile communication to deeply study the process and system function design of combining geographic information systems with multi-source remote sensing data in mobile communication network monitoring and management. On this basis, this study designed and implemented a dynamic updated terrain database for mobile communication. This database can update geographic information data in real-time, ensuring the timeliness and accuracy of the data. At the same time, by optimizing the database structure and query algorithms, the speed and efficiency of data processing have been improved, providing efficient and reliable solutions for coverage prediction, optimization analysis, and planning management of large-scale mobile communication networks.In summary, dynamic updating database of three-dimensional digital geographic information has important application value in mobile communication network simulation technology. Through in-depth research and application of this database, the performance and service quality of mobile communication networks can be effectively improved, laying a solid foundation for future communication technology development.

Underground Target Extraction by Local Entropy Feature of Voxelized 3D Ground Penetrating Radar

Abstract. To solve the current problem of insufficient exploration of three-dimensional spatial information detected by 3D ground penetrating radar (3D GPR) and the data processing mainly based on the analysis and interpretation of two-dimensional slice images, a method is proposed to extract underground target based on the local entropy feature of discrete point clouds after the voxelization of 3D GPR data. First, the acquired 3D GPR data was voxelized into discrete three-dimensional point clouds. Then the local entropy feature of the voxelized point clouds over the entire region were calculated. The soil background and underground targets were distinguished by classifying them from multiple dimensions through Support Vector Machine (SVM). Finally, the urban road underground environment was taken as the research object, and this method was used for experimental analysis using measured data. The experimental results show that the accuracy of this method in extracting underground targets is as high as 90.1%, and the missing detection rate of missing underground targets is as low as 7.8%. The proposed method is accurate and effective, providing a new approach for 3D GPR to extract underground target.

PharmaCore: The Automatic Generation of 3D Structure-Based Pharmacophore Models from Protein/Ligand Complexes.

In this work, we present PharmaCore: a new, completely automatic workflow aimed at generating three-dimensional (3D) structure-based pharmacophore models toward any target of interest. The proposed approach relies on using cocrystallized ligands to create the input files for generating the pharmacophore hypotheses, integrating not only the three-dimensional structural information on the ligand but also data concerning the binding mode of these molecules put in the protein cavity. We developed a Python library that, starting from the specific UniProt ID of the protein under investigation as the only element that requires user intervention, subsequently collects and aligns the corresponding structures bearing a known ligand in a fully automated fashion, bringing them all into the same coordinate system. The protocol includes a final phase in which the aligned small molecules are used to produce the pharmacophore hypotheses directly onto the protein structure using a specific software, e.g., Phase (Schrödinger LLC). To validate the entire procedure and highlight the possible applications in the field of drug discovery and repositioning, we first generated pharmacophores for soluble epoxide hydrolase (sEH) and compared with already-published ones. Then, we reproduced the binding profile of a reported selective binder of ATAD2 bromodomain (AM879), testing it against a panel of 1741 pharmacophores related to 16 epigenetic proteins and automatically generated with PharmaCore, finally disclosing putative unprecedented off-targets. The computational predictions were successfully validated with AlphaScreen assays, highlighting the applicability of the proposed workflow in drug discovery and repositioning. Finally, the process was also validated on tankyrase 2 and SARS-CoV-2 MPro, confirming the robustness of PharmaCore.

Investigation on the growth behaviour of creep crack in 2219 aluminium alloy by nanometre computed tomography

Aluminium alloy is widely utilized in aerospace engineering because of its lightweight and high specific strength. Creep and fracture of aluminium alloy serving at high-temperature conditions are always a long-term concern. Especially creep crack nucleation and growth behaviours under high out-of-plane constraint levels are the significant processes to generate failure. High-resolution nanometre computed tomography equipment can be adopted for obtaining the three-dimensional morphology and information on damage to investigate the mechanism of creep crack growth. According to the obtained results, the stress-field strength has an impact on creep crack propagation under high out-of-plane constraint levels.

Characterization of Al2O3 coating of Nb fiber-reinforced TiAl composite

The Al2O3 coating was synthesized on surface of the Nb fiber via cathodic plasma electrolytic deposition (CPED) method. The microstructure and composition of the coating were elaborately analyzed. The results revealed that compact and uniform Al2O3 is fully contact with TiAl matrix and Nb fiber, which was composed of κ-Al2O3 and α-Al2O3 and successfully hold back the oxidation reactions at the juncture and refrain from formation of detrimental phases. Especially, three-dimensional characterization information can be obtained from two-dimensional converging beam electron diffraction (CBED) pattern, from which the crystal constants of Al2O3 can be obtained directly under only one applicable zone axis.

Airborne Platform Three-Dimensional Positioning Method Based on Interferometric Synthetic Aperture Radar Interferogram Matching

As the demand for precise navigation of aircraft increases in modern society, researching high-precision, high-autonomy navigation systems is both theoretically valuable and practically significant. Because the inertial navigation system (INS) has systematic and random errors, its output information diverges. Therefore, it is necessary to combine them with other navigation systems for real-time compensation and correction of these errors. The SAR matching positioning and navigation system uses synthetic aperture radar (SAR) image matching for platform positioning and compensates for the drift caused by errors in the inertial measurement unit (IMU). Images obtained by SAR are matched with digital landmark data, and the platform’s position is calculated based on the SAR imaging geometry. However, SAR matching positioning faces challenges due to seasonal variations in SAR images, the need for typical landmarks for matching, and the lack of elevation information in two-dimensional SAR image matching. This paper proposes an airborne platform positioning method based on interferometric SAR (InSAR) interferogram matching. InSAR interferograms contain terrain elevation information, are less affected by seasonal changes, and provide higher positioning accuracy and robustness. By matching real-time InSAR-processed interferograms with simulated interferograms using a digital elevation model (DEM), three-dimensional position information about the matching points has been obtained. Subsequently, a three-dimensional positioning model for the platform has bene established using the unit line-of-sight vector decomposition method. In actual flight experiments using an FMCW Ku-band Interferometric SAR system, the proposed platform positioning framework demonstrated its ability to achieve precise positioning in the absence of signals from the global navigation satellite system (GNSS).

MAPPING 3D STRUCTURE OF URBAN TREES USING AIRBORNE LIDAR DATA FOR TOPOGRAPHIC SURVEY

Abstract. The designing of urban spaces utilizing trees is a promising approach to alleviate the severe thermal environment. Three-dimensional (3D) information on individual trees is important for their maintenance and for evaluating their microclimatic effects. Methods have been developed for estimating the 3D distribution of leaf area density (LAD) using high-density airborne light detection and ranging (LiDAR) point cloud. However, the coverage of high-density data is limited. This study sought to develop a method for estimating LAD distribution using existing low-density LiDAR data that was obtained for the nationwide topographic survey. A point cloud with the same density as the existing data was generated from the high-density data. LAD was estimated using the generated point cloud and was compared with LAD derived from the high-density data and terrestrial LiDAR to clarify the spatial scale of information obtained from the existing data. A method to improve the spatial scale was also examined. These methods were applied to the actual existing LiDAR data to generate a 3D information map at an urban scale.

Three-dimensional information measurement and reconstruction for micro-hole array based on the modified shape from focus

The geometrical characteristics of the micro-holes and the consistency of spatial distribution among the micro-holes in the micro-hole array fabricated by laser beam drilling (LBD) directly influence the cooling performance, reliability, and longevity of the workpiece. It is of great significance to establish the relationship between the LBD processing parameters and the characteristics of the micro-hole array through the three-dimensional (3D) information measurement and reconstruction of the micro-hole array, as well as to guide and improve the LBD processing technology. However, due to the small size and high aspect ratio of the micro-holes in the micro-hole array, the 3D information measurement and reconstruction of the micro-hole array face challenges. The conventional micro-hole measurement methods suffer from low efficiency, high measurement costs, and potentially destructive measurement processes. Furthermore, the conventional micro-hole measurement methods face challenges in simultaneously obtaining the geometrical characteristics of the micro-holes and the spatial distribution among the micro-holes in the micro-hole array. Therefore, a non-contact and non-destructive 3D information measurement and reconstruction method for the micro-hole array based on the modified shape from focus is proposed. A novel focus measure operator based on grayscale difference and adaptive neighborhood size is proposed to accurately evaluate the focus value and obtain the initial focus volume matrix. A novel image processing operator based on the gradient information of the image sequence is proposed to enhance the initial focus volume matrix. The experimental results indicate that the proposed focus measure operator, combined with the novel image processing operator, is more suitable and reliable for detecting the micro-holes due to its better unimodality, higher contrast, and narrower peak width than the conventional focus measure operator. The optimal focus position of each image point is obtained using the modified Gaussian curve fitting method. On this basis, the 3D information measurement and reconstruction of the micro-hole array are realized. By comparing the results with the conventional micro-hole measurement method, the feasibility and accuracy of the proposed method have been confirmed to be an effective measurement method for the micro-hole array.

Measuring canopy morphology of saltmarsh plant patches using UAV-based LiDAR data

Plant patches play a crucial role in understanding the biogeomorphology of saltmarshes. Although two-dimensional optical remote sensing has long been applied to the study of saltmarsh plant patches, studies focusing on the canopy features at a patch-scale remain limited. Therefore, a simple and efficient method is needed to capture three-dimensional patch features and their relationship to habitat. This study utilized UAV-based LiDAR to obtain three-dimensional patch features of the native species S. mariqueter and the invasive species S. alterniflora in Andong Shoal, Hangzhou Bay, and examine the relationship between patch distribution and geomorphological characteristics. A workflow was established to overcome the inability of low-cost LiDAR sensor to penetrate dense vegetation, resulting in no ground return. Results showed that S. alterniflora patches were smaller in size but taller in canopy height than S. mariqueter patches. Regarding morphological patterns of patch canopy, S. alterniflora exhibited single-arch patterns (29%) and double-arch patterns (16%), whereas S. mariqueter exhibited only single-arch patterns (83%). The presence of double-arch patches suggested the development of fairy circles, indicating that the invasive S. alterniflora exhibits greater ecological resilience compared to the native S. mariqueter. Furthermore, this study explored the ecological niches of the two species in the pioneer zone of Andong Shoal. The ecological niches for S. alterniflora were 2.00-2.25 m, whereas that for S. mariqueter were 1.85-2.00 m and 2.25-2.40 m. Distance from the tidal creeks significantly moderated the number and area of patches for both species. This study demonstrated that UAV-based LiDAR technology can provide high-quality three-dimensional information about the pioneer zone of saltmarsh, thus helping to understand biogeomorphological processes in this region.

Structural analysis of the female reptile reproductive system by micro-computed tomography and optical coherence tomography†.

Volumetric data provide unprecedented structural insight to the reproductive tract and add vital anatomical context to the relationships between organs. The morphology of the female reproductive tract in non-avian reptiles varies between species, corresponding to a broad range of reproductive modes and providing valuable insight to comparative investigations of reproductive anatomy. However, reproductive studies in reptilian models, such as the brown anole studied here, have historically relied on histological methods to understand the anatomy. While these methods are highly effective for characterizing the cell types present in each organ, histological methods lose the 3D relationships between images and leave the architecture of the organ system poorly understood. We present the first comprehensive volumetric analyses of the female brown anole reproductive tract using two non-invasive, non-destructive imaging modalities: micro-computed tomography (microCT) and optical coherence tomography (OCT). Both are specialized imaging technologies that facilitate high-throughput imaging and preserve three-dimensional information. This study represents the first time that microCT has been used to study all reproductive organs in this species and the very first time that OCT has been applied to this species. We show how the non-destructive volumetric imaging provided by each modality reveals anatomical context including orientation and relationships between reproductive organs of the anole lizard. In addition to broad patterns of morphology, both imaging modalities provide the high resolution necessary to capture details and key anatomical features of each organ. We demonstrate that classic histological features can be appreciated within whole-organ architecture in volumetric imaging using microCT and OCT, providing the complementary information necessary to understand the relationships between tissues and organs in the reproductive system. This side-by-side imaging analysis using microCT and OCT allows us to evaluate the specific advantages and limitations of these two methods for the female reptile reproductive system.

Hybrid watermarking and encryption techniques for securing three-dimensional information

A hybrid digital watermarking and encryption technique based on the Computer Generated Holography (CGH) and fractional Fourier transform (FRFT) combined with singular value decomposition (SVD) algorithm is proposed for securing three-dimensional (3D) information. Initially, hierarchical 3D information is encrypted using the angular spectrum diffraction method and a random phase key. This process yields a binary real valued CGH, where incorporating a random phase key broadens the key space and adds complexity, effectively scrambling and concealing the 3D information. Subsequently, the encrypted binary real valued CGH is embedded into the host image as a watermark using the FRFT-SVD algorithm. This hybrid approach enhances the security of the watermarking process. In the final step, the CGH watermark is extracted using the inverse operation of the embedding algorithm. Applying the correct optical key and angular spectrum inverse algorithm successfully reconstructs the 3D information. The watermark algorithm’s efficiency significantly improves by leveraging the rapid computational speed and high focusing capabilities of the FRFT. Additionally, integrating SVD enhances the image’s resistance to geometric attacks, thereby improving the algorithm’s invisibility and robustness. The proposed scheme effectively achieves the encryption and digital watermarking of 3D information. Simulation results substantiate the presented watermarking scheme’s efficacy and robustness.

Augmented reality presentation system of skeleton image based on biomedical features

Aimed at limitations in the description and expression of three-dimensional (3D) physical information in two-dimentsional (2D) medical images, feature extraction and matching method based on the biomedical characteristics of skeletons is employed in this paper to map the 2D images of skeletons into a 3D digital model. Augmented reality technique is used to realize the interactive presentation of skeleton models. Main contents of this paper include: Firstly, a three-step reconstruction method is used to process the bone CT image data to obtain its three-dimensional surface model, and the corresponding 2D–3D bone library is established based on the identification index of the 2D image and the 3D model; then, a fast and accurate feature extraction and matching algorithm is developed to realize the recognition, extraction, and matching of 2D skeletal features, and determine the corresponding 3D skeleton model according to the matching result. Finally, based on the augmented reality technique, an interactive immersive presentation system is designed to achieve visual effects of the virtual human bone model superimposed and rendered in the world scenes, which improves the effectiveness of information expression and transmission, as well as the user's immersion and embodied experience.