Sparse-view neutron CT 3D image reconstruction algorithm based on split Bregman method

As a complement to X-ray computed tomography(CT),neutron tomography has been extensively used in nuclear engineer-ing,materials science,cultural heritage,and industrial applications.Reconstruction of the attenuation matrix for neutron tomography with a traditional analytical algorithm requires hundreds of projection views in the range of 0°to 180°and typically takes several hours to complete.Such a low time-resolved resolution degrades the quality of neutron imaging.Decreasing the number of projection acquisitions is an important approach to improve the time resolution of images;however,this requires efficient reconstruction algorithms.Therefore,sparse-view reconstruction algorithms in neutron tomography need to be investigated.In this study,we investigated the three-dimensional reconstruction algorithm for sparse-view neu-tron CT scans.To enhance the reconstructed image quality of neutron CT,we propose an algorithm that uses OS-SART to reconstruct images and a split Bregman to solve for the total variation(SBTV).A comparative analysis of the performances of each reconstruction algorithm was performed using simulated and actual experimental data.According to the analyzed results,OS-SART-SBTV is superior to the other algorithms in terms of denoising,suppressing artifacts,and preserving detailed structural information of images.

SAR regional all-azimuth observation orbit design for target 3D reconstruction

Three-dimensional(3D) synthetic aperture radar(SAR)extends the conventional 2D images into 3D features by several acquisitions in different aspects. Compared with 3D techniques via multiple observations in elevation, e.g. SAR interferometry(InSAR) and SAR tomography(TomoSAR), holographic SAR can retrieve 3D structure by observations in azimuth. This paper focuses on designing a novel type of orbit to achieve SAR regional all-azimuth observation(AAO) for embedded targets detection and holographic 3D reconstruction. The ground tracks of the AAO orbit separate the earth surface into grids. Target in these grids can be accessed with an azimuth angle span of360°, which is similar to the flight path of airborne circular SAR(CSAR). Inspired from the successive coverage orbits of optical sensors, several optimizations are made in the proposed method to ensure favorable grazing angles, the performance of 3D reconstruction, and long-term supervision for SAR sensors. Simulation experiments show the regional AAO can be completed within five hours. In addition, a second AAO of the same area can be duplicated in two days. Finally, an airborne SAR data process result is presented to illustrate the significance of AAO in 3D reconstruction.

Efficacy of laparoscopic low anterior resection for colorectal cancer patients with 3D-vascular reconstruction for left coronary artery preservation

BACKGROUND Laparoscopic low anterior resection(LLAR)has become a mainstream surgical method for the treatment of colorectal cancer,which has shown many advantages in the aspects of surgical trauma and postoperative rehabilitation.However,the effect of surgery on patients'left coronary artery and its vascular reconstruction have not been deeply discussed.With the development of medical imaging technology,3D vascular reconstruction has become an effective means to evaluate the curative effect of surgery.AIM To investigate the clinical value of preoperative 3D vascular reconstruction in LLAR of rectal cancer with the left colic artery(LCA)preserved.METHODS A retrospective cohort study was performed to analyze the clinical data of 146 patients who underwent LLAR for rectal cancer with LCA preservation from January to December 2023 in our hospital.All patients underwent LLAR of rectal cancer with the LCA preserved,and the intraoperative and postoperative data were complete.The patients were divided into a reconstruction group(72 patients)and a nonreconstruction group(74 patients)according to whether 3D vascular reconstruction was performed before surgery.The clinical features,operation conditions,complications,pathological results and postoperative recovery of the two groups were collected and compared.RESULTS A total of 146 patients with rectal cancer were included in the study,including 72 patients in the reconstruction group and 74 patients in the nonreconstruction group.There were 47 males and 25 females in the reconstruction group,aged(59.75±6.2)years,with a body mass index(BMI)(24.1±2.2)kg/m^(2),and 51 males and 23 females in the nonreconstruction group,aged(58.77±6.1)years,with a BMI(23.6±2.7)kg/m^(2).There was no significant difference in the baseline data between the two groups(P>0.05).In the submesenteric artery reconstruction group,35 patients were type Ⅰ,25 patients were type Ⅱ,11 patients were type Ⅲ,and 1 patient was type Ⅳ.There were 37 type Ⅰ patients,24 type Ⅱ patients,12 type Ⅲ patients,and 1 type Ⅳ patient in the nonreconstruction group.There was no significant difference in arterial typing between the two groups(P>0.05).The operation time of the reconstruction group was 162.2±10.8 min,and that of the nonreconstruction group was 197.9±19.1 min.Compared with that of the reconstruction group,the operation time of the two groups was shorter,and the difference was statistically significant(t=13.840,P<0.05).The amount of intraoperative blood loss was 30.4±20.0 mL in the reconstruction group and 61.2±26.4 mL in the nonreconstruction group.The amount of blood loss in the reconstruction group was less than that in the control group,and the difference was statistically significant(t=-7.930,P<0.05).The rates of anastomotic leakage(1.4%vs 1.4%,P=0.984),anastomotic hemorrhage(2.8%vs 4.1%,P=0.672),and postoperative hospital stay(6.8±0.7 d vs 7.0±0.7 d,P=0.141)were not significantly different between the two groups.CONCLUSION Preoperative 3D vascular reconstruction technology can shorten the operation time and reduce the amount of intraoperative blood loss.Preoperative 3D vascular reconstruction is recommended to provide an intraoperative reference for laparoscopic low anterior resection with LCA preservation.

Accurate resection of hilar cholangiocarcinoma using eOrganmap 3D reconstruction and full quantization technique

BACKGROUND For treatment of hilar cholangiocarcinoma(HCCA),the rate of radical resection is low and prognosis is poor,and preoperative evaluation is not sufficiently accurate.3D visualization has the advantage of giving a stereoscopic view,which makes accurate resection of HCCA possible.AIM To establish precise resection of HCCA based on eOrganmap 3D reconstruction and full quantification technology.METHODS We retrospectively analyzed the clinical data of 73 patients who underwent HCCA surgery.All patients were assigned to two groups.The traditional group received traditional 2D imaging planning before surgery(n=35).The eOrganmap group underwent 3D reconstruction and full quantitative technical planning before surgery(n=38).The preoperative evaluation,anatomical classification of hilar hepatic vessels,indicators associated with surgery,postoperative complications,liver function,and stress response indexes were compared between the groups.RESULTS Compared with the traditional group,the amount of intraoperative blood loss in the eOrganmap group was lower,the operating time and postoperative intestinal ventilation time were shorter,and R0 resection rate and lymph node dissection number were higher(P<0.05).The total complication rate in the eOrganmap group was 21.05%compared with 25.71%in the traditional group(P>0.05).The levels of total bilirubin,Albumin(ALB),aspartate transaminase,and alanine transaminase in the eOrganmap group were significantly different from those in the traditional group(intergroup effect:F=450.400,79.120,95.730,and 13.240,respectively;all P<0.001).Total bilirubin,aspartate transaminase,and alanine transaminase in both groups showed a decreasing trend with time(time effect:F=30.270,17.340,and 13.380,respectively;all P<0.001).There was an interaction between patient group and time(interaction effect:F=3.072,2.965,and 2.703,respectively;P=0.0282,0.032,and 0.046,respectively);ALB levels in both groups tended to increase with time(time effect:F=22.490,P<0.001),and there was an interaction effect between groups and time(interaction effect:F=4.607,P=0.004).In the eOrganmap group,there was a high correlation between the actual volume of intraoperative liver specimen resection and the volume of preoperative virtual liver resection(t=0.916,P<0.001).CONCLUSION The establishment of accurate laparoscopic resection of hilar cholangiocarcinoma based on preoperative eOrganmap 3D reconstruction and full quantization technology can make laparoscopic resection of hilar cholangiocarcinoma more accurate and safe.

Preoperative 3D reconstruction and fluorescent indocyanine green for laparoscopic duodenum preserving pancreatic head resection:A case report

BACKGROUND Duodenum-preserving pancreatic head resection(DPPHR)is the choice of surgery for benign or low-grade malignant tumors of the pancreatic head.Laparoscopic DPPHR(LDPPHR)procedure can be improved by preoperative 3D model reconstruction and the use of intravenous indocyanine green fluorescent before surgery for real-time navigation with fluorescent display to guide the surgical dissection and prevention of from injury to vessels and biliary tract.CASE SUMMARY Here we report the successful short-and long-term outcomes after one year following LDPPHR for a 60-year lady who had an uneventful recovery and was discharged home one week after the surgery.CONCLUSION There was no bile leakage or pancreatic leakage or delayed gastric emptying.The histopathology report showed multiple cysts in the pancreatic head and localized pancreatic intraepithelial tumor lesions.The resected margin was free of tumor.

3D Reconstruction for Motion Blurred Images Using Deep Learning-Based Intelligent Systems

The 3D reconstruction using deep learning-based intelligent systems can provide great help for measuring an individual’s height and shape quickly and accurately through 2D motion-blurred images.Generally,during the acquisition of images in real-time,motion blur,caused by camera shaking or human motion,appears.Deep learning-based intelligent control applied in vision can help us solve the problem.To this end,we propose a 3D reconstruction method for motion-blurred images using deep learning.First,we develop a BF-WGAN algorithm that combines the bilateral filtering(BF)denoising theory with a Wasserstein generative adversarial network(WGAN)to remove motion blur.The bilateral filter denoising algorithm is used to remove the noise and to retain the details of the blurred image.Then,the blurred image and the corresponding sharp image are input into the WGAN.This algorithm distinguishes the motion-blurred image from the corresponding sharp image according to the WGAN loss and perceptual loss functions.Next,we use the deblurred images generated by the BFWGAN algorithm for 3D reconstruction.We propose a threshold optimization random sample consensus(TO-RANSAC)algorithm that can remove the wrong relationship between two views in the 3D reconstructed model relatively accurately.Compared with the traditional RANSAC algorithm,the TO-RANSAC algorithm can adjust the threshold adaptively,which improves the accuracy of the 3D reconstruction results.The experimental results show that our BF-WGAN algorithm has a better deblurring effect and higher efficiency than do other representative algorithms.In addition,the TO-RANSAC algorithm yields a calculation accuracy considerably higher than that of the traditional RANSAC algorithm.

Fast Estimation of Loader’s Shovel Load Volume by 3D Reconstruction of Material Piles

Fast and accurate measurement of the volume of earthmoving materials is of great signifcance for the real-time evaluation of loader operation efciency and the realization of autonomous operation. Existing methods for volume measurement, such as total station-based methods, cannot measure the volume in real time, while the bucket-based method also has the disadvantage of poor universality. In this study, a fast estimation method for a loader’s shovel load volume by 3D reconstruction of material piles is proposed. First, a dense stereo matching method (QORB–MAPM) was proposed by integrating the improved quadtree ORB algorithm (QORB) and the maximum a posteriori probability model (MAPM), which achieves fast matching of feature points and dense 3D reconstruction of material piles. Second, the 3D point cloud model of the material piles before and after shoveling was registered and segmented to obtain the 3D point cloud model of the shoveling area, and the Alpha-shape algorithm of Delaunay triangulation was used to estimate the volume of the 3D point cloud model. Finally, a shovel loading volume measurement experiment was conducted under loose-soil working conditions. The results show that the shovel loading volume estimation method (QORB–MAPM VE) proposed in this study has higher estimation accuracy and less calculation time in volume estimation and bucket fll factor estimation, and it has signifcant theoretical research and engineering application value.

3D Echocardiogram Reconstruction Employing a Flip Directional Texture Pyramid

Three dimensional(3D)echocardiogram enables cardiologists to visua-lize suspicious cardiac structures in detail.In recent years,this three-dimensional echocardiogram carries important clinical value in virtual surgical simulation.However,this 3D echocardiogram involves a trade-off difficulty between accu-racy and efficient computation in clinical diagnosis.This paper presents a novel Flip Directional 3D Volume Reconstruction(FD-3DVR)method for the recon-struction of echocardiogram images.The proposed method consists of two main steps:multiplanar volumetric imaging and 3D volume reconstruction.In the crea-tion of multiplanar volumetric imaging,two-dimensional(2D)image pixels are mapped into voxels of the volumetric grid.As the obtained slices are discontin-uous,there are some missing voxels in the volume data.To restore the structural and textural information of 3D ultrasound volume,the proposed method creates a volume pyramid in parallel with theflip directional texture pyramid.Initially,the nearest neighbors of missing voxels in the multiplanar volumetric imaging are identified by 3D ANN(Approximate Nearest Neighbor)patch matching method.Furthermore,aflip directional texture pyramid is proposed and aggregated with distance in patch matching tofind out the most similar neighbors.In the recon-struction step,structural and textural information obtained from differentflip angle directions can reconstruct 3D volume well with the desired accuracy.Com-pared with existing 3D reconstruction methods,the proposed Flip Directional 3D Volume Reconstruction(FD-3DVR)method provides superior performance for the mean peak signal-to-noise ratio(40.538 for the proposed method I and 39.626 for the proposed method II).Experimental results performed on the cardi-ac datasets demonstrate the efficiency of the proposed method for the reconstruc-tion of echocardiogram images.

Three-dimensional(3D)parametric measurements of individual gravels in the Gobi region using point cloud technique

Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.

Generating animatable 3D cartoon faces from single portraits

Background With the development of virtual reality(VR)technology,there is a growing need for customized 3D avatars.However,traditional methods for 3D avatar modeling are either time-consuming or fail to retain the similarity to the person being modeled.This study presents a novel framework for generating animatable 3D cartoon faces from a single portrait image.Methods First,we transferred an input real-world portrait to a stylized cartoon image using StyleGAN.We then proposed a two-stage reconstruction method to recover a 3D cartoon face with detailed texture.Our two-stage strategy initially performs coarse estimation based on template models and subsequently refines the model by nonrigid deformation under landmark supervision.Finally,we proposed a semantic-preserving face-rigging method based on manually created templates and deformation transfer.Conclusions Compared with prior arts,the qualitative and quantitative results show that our method achieves better accuracy,aesthetics,and similarity criteria.Furthermore,we demonstrated the capability of the proposed 3D model for real-time facial animation.

3D reconstruction of worn parts for flexible remanufacture based on robotic arc welding

3D reconstruction of worn parts is the foundation for remanufacturing system based on robotic arc welding, because it can provide 3D geometric information for robot task plan. In this investigation, a novel 3D reconstruction system based on linear structured light vision sensing is developed. This system hardware consists of a MTC368-CB CCD camera, a MLH-645 laser projector and a DH-CG300 image grabbing card. This system software is developed to control the image data capture. In order to reconstruct the 3D geometric information from the captured image, a two steps rapid calibration algorithm is proposed. The 3D reconstruction experiment shows a satisfactory result.

3D Shape Reconstruction of Lumbar Vertebra From Two X-ray Images and a CT Model

Structure reconstruction of 3 D anatomy from biplanar X-ray images is a challenging topic. Traditionally, the elastic-model-based method was used to reconstruct 3 D shapes by deforming the control points on the elastic mesh. However, the reconstructed shape is not smooth because the limited control points are only distributed on the edge of the elastic mesh.Alternatively, statistical-model-based methods, which include shape-model-based and intensity-model-based methods, are introduced due to their smooth reconstruction. However, both suffer from limitations. With the shape-model-based method, only the boundary profile is considered, leading to the loss of valid intensity information. For the intensity-based-method, the computation speed is slow because it needs to calculate the intensity distribution in each iteration. To address these issues, we propose a new reconstruction method using X-ray images and a specimen’s CT data. Specifically, the CT data provides both the shape mesh and the intensity model of the vertebra. Intensity model is used to generate the deformation field from X-ray images, while the shape model is used to generate the patient specific model by applying the calculated deformation field.Experiments on the public synthetic dataset and clinical dataset show that the average reconstruction errors are 1.1 mm and1.2 mm, separately. The average reconstruction time is 3 minutes.

Uses of a dedicated 3D reconstruction software with augmented and mixed reality in planning and performing advanced liver surgery and living donor liver transplantation(with videos)

The development of digital intelligent diagnostic and treatment technology has opened countless new opportunities for liver surgery from the era of digital anatomy to a new era of digital diagnostics,virtual surgery simulation and using the created scenarios in real-time surgery using mixed reality.In this article,we described our experience on developing a dedicated 3 dimensional visualization and reconstruction software for surgeons to be used in advanced liver surgery and living donor liver transplantation.Furthermore,we shared the recent developments in the field by explaining the outreach of the software from virtual reality to augmented reality and mixed reality.

Deep-Learning-Empowered 3D Reconstruction for Dehazed Images in IoT-Enhanced Smart Cities

With increasingly more smart cameras deployed in infrastructure and commercial buildings,3D reconstruction can quickly obtain cities’information and improve the efficiency of government services.Images collected in outdoor hazy environments are prone to color distortion and low contrast;thus,the desired visual effect cannot be achieved and the difficulty of target detection is increased.Artificial intelligence(AI)solutions provide great help for dehazy images,which can automatically identify patterns or monitor the environment.Therefore,we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning.First,we propose a fine transmission image deep convolutional regression network(FT-DCRN)dehazing algorithm that uses fine transmission image and atmospheric light value to compute dehazed image.The DCRN is used to obtain the coarse transmission image,which can not only expand the receptive field of the network but also retain the features to maintain the nonlinearity of the overall network.The fine transmission image is obtained by refining the coarse transmission image using a guided filter.The atmospheric light value is estimated according to the position and brightness of the pixels in the original hazy image.Second,we use the dehazed images generated by the FT-DCRN dehazing algorithm for 3D reconstruction.An advanced relaxed iterative fine matching based on the structure from motion(ARI-SFM)algorithm is proposed.The ARISFM algorithm,which obtains the fine matching corner pairs and reduces the number of iterations,establishes an accurate one-to-one matching corner relationship.The experimental results show that our FT-DCRN dehazing algorithm improves the accuracy compared to other representative algorithms.In addition,the ARI-SFM algorithm guarantees the precision and improves the efficiency.

Application of computer tomography-based 3D reconstruction technique in hernia repair surgery

BACKGROUND Hernia is a common condition requiring abdominal surgery.The current standard treatment for hernia is tension-free repair using meshes.Globally,more than 200 new types of meshes are licensed each year.However,their clinical applications are associated with a series of complications,such as recurrence(10%-24%)and infection(0.5%-9.0%).In contrast,3D-printed meshes have significantly reduced the postoperative complications in patients.They have also shortened operating time and minimized the loss of mesh materials.In this study,we used the myopectineal orifice(MPO)data obtained from preoperative computer tomography(CT)-based 3D reconstruction for the production of 3D-printed biologic meshes.AIM To investigate the application of multislice spiral CT-based 3D reconstruction technique in 3D-printed biologic mesh for hernia repair surgery.METHODS We retrospectively analyzed 60 patients who underwent laparoscopic tension-free repair for inguinal hernia in the Department of General Surgery of the First Hospital of Shanxi Medical University from September 2019 to December 2019.This study included 30 males and 30 females,with a mean age of 40±5.6 years.Data on the MPO were obtained from preoperative CT-based 3D reconstruction as well as from real-world intraoperative measurements for all patients.Anatomic points were set for the purpose of measurement based on the definition of MPO:A:The pubic tubercle;B:Intersection of the horizontal line extending from the summit of the inferior edge of the internal oblique and transversus abdominis and the outer edge of the rectus abdominis,C:Intersection of the horizontal line extending from the summit of the inferior edge of the internal oblique and transversus abdominis and the inguinal ligament,D:Intersection of the iliopsoas muscle and the inguinal ligament,and E:Intersection of the iliopsoas muscle and the superior pubic ramus.The distance between the points was measured.All preoperative and intraoperative data were analyzed using the t test.Differences with P<0.05 were considered significant in comparative analysis.RESULTS The distance between points AB,AC,BC,DE,and AE based on preoperative and intraoperative data was 7.576±0.212 cm vs 7.573±0.266 cm,7.627±0.212 cm vs 7.627±0.212 cm,7.677±0.229 cm vs 7.567±0.786 cm,7.589±0.204 cm vs 7.512±0.21 cm,and 7.617±0.231 cm vs 7.582±0.189 cm,respectively.All differences were not statistically significant(P>0.05).CONCLUSION The use of multislice spiral CT-based 3D reconstruction technique before hernia repair surgery allows accurate measurement of data and relationships of different anatomic sites in the MPO region.This technique can provide precise data for the production of 3D-printed biologic meshes.

PCA-based 3D Shape Reconstruction of Human Foot Using Multiple Viewpoint Cameras

This paper describes a multiple camera-based method to reconstruct the 3D shape of a human foot. From a foot database, an initial 3D model of the foot represented by a cloud of points is built. The shape parameters, which can characterize more than 92% of a foot, are defined by using the principal component analysis method. Then, using ＂active shape models＂, the initial 3D model is adapted to the real foot captured in multiple images by applying some constraints （edge points＇ distance and color variance）. We insist here on the experiment part where we demonstrate the efficiency of the proposed method on a plastic foot model, and also on real human feet with various shapes. We propose and compare different ways of texturing the foot which is needed for reconstruction. We present an experiment performed on the plastic foot model and on human feet and propose two different ways to improve the final 3D shapers accuracy according to the previous experiments＇ results. The first improvement proposed is the densification of the cloud of points used to represent the initial model and the foot database. The second improvement concerns the projected patterns used to texture the foot. We conclude by showing the obtained results for a human foot with the average computed shape error being only 1.06 mm.

3D motion and geometric information system of single-antenna radar based on incomplete 1D range data

A 3D motion and geometric information system of single-antenna radar is proposed,which can be supported by spotlight synthetic aperture radar（SAR） system and inverse SAR（ISAR） system involving relative 3D motion of the rigid target.In this system,applying the geometry invariance of the rigid target,the unknown 3D shape and motion of the radar target can be reconstructed from the 1D range data of some scatterers extracted from the high-resolution range image.Compared with the current 1D-to-3D algorithm,in the proposed algorithm,the requirement of the 1D range data is expanded to incomplete formation involving large angular motion of the target and hence,the quantity of the scatterers and the abundance of 3D motion are enriched.Furthermore,with the three selected affine coordinates fixed,the multi-solution problem of the reconstruction is solved and the technique of nonlinear optimization can be successfully utilized in the system.Two simulations are implemented which verify the higher robustness of the system and the better performance of the 3D reconstruction for the radar target with unknown relative motion.

3D surface reconstruction based on binocular vision using structured light

A 3D surface reconstruction method using a binocular stereo vision technology and a coded structured light,which combines a gray code with phase-shift has been studied.The accuracy of the 3 D surface reconstruction mainly depends on the decoding of gray code views and phase-shift views.In order to find the boundary accurately,gray code patterns and their inverses are projected onto a human eye plaster model.The period dislocation between the gray code views and the phase-shift views in the course of decoding has been analyzed and a new method has been proposed to solve it.The splicing method is based on feature points.The result of the 3D surface reconstruction shows the accuracy and reliability of our method.

MULTIPARAMETER MEASUREMENT FOR RACEWAY GROOVE OF BEARING BASED ON 3D RECONSTRUCTION WITH DIGITAL STRUCTURED LIGHT

A fast 3D reconstruction method based on structured light to measure various parameters of the raceway groove is presented. Digital parallel grating stripes distributed with sine density are projected onto the raceway groove by a DLP projector, and distorting of stripes is happened on the raceway. Simultaneously, aided by three-step phase-shifting approach, three images covered by different stripes are obtained by a high-resolution CCD camera at the same location, thus a more accuracy local topography can be obtained. And then the bearing is rotated on a high precision computer controlled rotational stage. Three images are also obtained as the former step at next planned location triggered by the motor. After one cycle, all images information is combined through the mosaics. As a result, the 3D information of raceway groove can be gained. Not only geometric properties but also surface flaws can be extracted by software. A preliminary hardware system has been built, with which some geometric parameters have been extracted from reconstructed local topography.

3D Reconstruction by Kinect Sensor:A Brief Review

While Kinect was originally designed as a motion sensing input device of the gaming console Microsoft Xbox 360 for gaming purposes, it＇s easy-to-use, low-cost, reliability, speed of the depth measurement and relatively high quality of depth measurement make it can be used for 3D reconstruction. It could make 3D scanning technology more accessible to everyday users and turn 3D reconstruction models into much widely used asset for many applications. In this paper, we focus on Kinect 3D reconstruction.