scholarly journals Surface reconstruction based on the camera relative irradiance

2018 ◽  
Vol 14 (2) ◽  
pp. 155014771875956 ◽  
Author(s):  
Bin Yao ◽  
Weifang Sun ◽  
Binqiang Chen ◽  
Tianxiang Zhou ◽  
Xincheng Cao
Keyword(s):  
Surface Reconstruction ◽  
Three Dimensional ◽  
Reconstruction Error ◽  
Reconstruction Method ◽  
Gray Scale ◽  
Reconstruction Process ◽  
Charge Coupled Device ◽  
Calibration Process ◽  
Dimensional Measurements ◽  
Illumination Measurement

Precise three-dimensional measurements of surfaces are significant in many fields. Usually, three-dimensional descriptions of the object surface have to be acquired by contact measure probe or other non-contact equipment. The paper proposed a novel surface reconstruction method that uses camera relative irradiance via the image gray-scale value information under fixed ring light. After calibrations of the measurement condition, just one image of the object is necessary to reconstruct the surface. The method mainly involves two aspects: the calibration process and the surface reconstruction process. The purpose of the calibration process is to find the relation between the image gray-scale value and the relative irradiance of the charge-coupled device sensor in different expose conditions. The surface reconstruction mainly focuses on the relation between the irradiance and height information. The experiment result shows the relative error of the illumination measurement result obtained using charge-coupled device camera is less than 2.91%. Reconstruction error is mainly result from the truncation error of algorithm calculation. An example is presented to verify the performance of this technique. The reconstruction experiments demonstrated that it can successfully measure the geometrical characteristics from the specified view of the object.

Material Surface Reconstruction Based on Light Projection

2010 ◽  
Vol 143-144 ◽  
pp. 768-772
Author(s):  
Shao Yan Gai ◽  
Fei Peng Da
Keyword(s):  
Surface Reconstruction ◽  
Three Dimensional ◽  
Shape Reconstruction ◽  
Material Surface ◽  
Reconstruction Method ◽  
Object Surface ◽  
Reconstruction Process ◽  
Dimensional Shape ◽  
Three Dimensional Shape ◽  
Vision Geometry

A surface reconstruction method for material shape analysis is presented. The three-dimensional shape reconstruction system detects object surface based on optical principle. A series of gratings are projected to the object, and the projected gratings are deformed by the object surface. From images of the deformed gratings, three-dimensional profile of the material surface can be obtained. The basic aspects of the method are discussed, including the vision geometry, the light projection and code principle. The proposed method can deal with objects with various discontinuities on the material surface, thus increasing the flexibility and robustness of shape reconstruction process. The experimental results show the efficiency of the method, the material surface can be reconstructed with high precision in various applications.

A novel three-dimensional surface reconstruction method for the complex fabrics based on the MVS

2020 ◽  
Vol 131 ◽  
pp. 106415
Author(s):  
Yiliang Wang ◽  
Na Deng ◽  
Binjie Xin ◽  
Wenzhen Wang ◽  
Wenyu Xing ◽  
...  
Keyword(s):  
Surface Reconstruction ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Dimensional Surface

scholarly journals Contour reconstruction of three-dimensional spiral CT damage image

2018 ◽  
Vol 11 (05) ◽  
pp. 1850028
Author(s):  
Ling-Ling Cui ◽  
Hui Zhang
Keyword(s):  
Feature Matching ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Spiral Ct ◽  
Reconstruction Error ◽  
Statistical Shape Model ◽  
Gradient Algorithm ◽  
Reconstruction Method ◽  
Contour Reconstruction ◽  
Contour Feature

In order to improve the diagnosis and analysis ability of 3D spiral CT and to reconstruct the contour of 3D spiral CT damage image, a contour reconstruction method based on sharpening template enhancement for 3D spiral CT damage image is proposed. This method uses the active contour LasSO model to extract the contour feature of the 3D spiral CT damage image and enhances the information by sharpening the template enhancement technique and makes the noise separation of the 3D spiral CT damage image. The spiral CT image was processed with ENT, and the statistical shape model of 3D spiral CT damage image was established. The gradient algorithm is used to decompose the feature to realize the analysis and reconstruction of the contour feature of the 3D spiral CT damage image, so as to improve the adaptive feature matching ability and the ability to locate the abnormal feature points. The simulation results show that in the 3D spiral CT damage image contour reconstruction, the proposed method performs well in the feature matching of the output pixels, shortens the contour reconstruction time by 20/ms, and provides a strong ability to express the image information. The normalized reconstruction error of CES is 30%, which improves the recognition ability of 3D spiral CT damage image, and increases the signal-to-noise ratio of peak output by 40 dB over other methods.

scholarly journals Degenerate Near-Planar 3D Reconstruction from Two Overlapped Images for Road Defects Detection

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1640
Author(s):  
Yazhe Hu ◽  
Tomonari Furukawa
Keyword(s):  
3D Reconstruction ◽  
Surface Defects ◽  
Three Dimensional ◽  
Recall Rate ◽  
Reconstruction Error ◽  
Vertical Movement ◽  
Road Surface ◽  
Reconstruction Process ◽  
The Road ◽  
Road Surfaces

This paper presents a technique to reconstruct a three-dimensional (3D) road surface from two overlapped images for road defects detection using a downward-facing camera. Since some road defects, such as potholes, are characterized by 3D geometry, the proposed technique reconstructs road surfaces from the overlapped images prior to defect detection. The uniqueness of the proposed technique lies in the use of near-planar characteristics of road surfaces‘ in the 3D reconstruction process, which solves the degenerate road surface reconstruction problem. The reconstructed road surfaces thus result from the richer information. Therefore, the proposed technique detects road surface defects based on the accuracy-enhanced 3D reconstruction. Parametric studies were first performed in a simulated environment to analyze the 3D reconstruction error affected by different variables and show that the reconstruction errors caused by the camera’s image noise, orientation, and vertical movement are so small that they do not affect the road defects detection. Detailed accuracy analysis then shows that the mean and standard deviation of the errors are less than 0.6 mm and 1 mm through real road surface images. Finally, on-road tests demonstrate the effectiveness of the proposed technique in identifying road defects while having over 94% in precision, accuracy, and recall rate.

FAST RECONSTRUCTION METHOD BASED ON COMMON UNIFIED DEVICE ARCHITECTURE (CUDA) FOR MICRO-CT

2010 ◽  
Vol 03 (01) ◽  
pp. 39-43 ◽  
Author(s):  
GUOTAO QUAN ◽  
TANGYOU SUN ◽  
YONG DENG
Keyword(s):  
Image Reconstruction ◽  
Graphics Processing Units ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Micro Ct ◽  
3D Image ◽  
Reconstruction Process ◽  
Device Architecture ◽  
3D Image Reconstruction ◽  
Fdk Algorithm

Three-dimensional image reconstruction with Feldkamp, Davis, and Kress (FDK) algorithm is the most time consuming part in Micro-CT. The parallel algorithm based on the computer cluster is capable of accelerating image reconstruction speed; however, the hardware is very expensive. In this paper, using the most current graphics processing units (GPU), we present a method based on common unified device architecture (CUDA) for speeding up the Micro-CT image reconstruction process. The most time consuming filtering and back-projection parts of the FDK algorithm are parallelized for the CUDA architecture. The CUDA-based reconstruction speed and image qualities are compared with CPU results for the projecting data of the Micro-CT system. The results show that the 3D image reconstruction speed based on CUDA is ten times faster than the speed with CPU. In conclusion the FDK algorithm based on CUDA for Micro-CT can reconstruct the 3D image right after the end of data acquisition.

Three-dimensional reconstruction of the 40S ribosomal subunit from rabbit reticulocytes

1987 ◽  
Vol 45 ◽  
pp. 936-937
Author(s):  
Neng-Yu Zhang ◽  
Terence Wagenknecht ◽  
Michael Radermacher ◽  
Tom Obrig ◽  
Joachim Frank
Keyword(s):  
Three Dimensional ◽  
Ribosomal Subunit ◽  
Uranyl Acetate ◽  
Reconstruction Method ◽  
Single Exposure ◽  
Electron Dose ◽  
Ribosomal Subunits ◽  
40S Ribosomal Subunit ◽  
Dimensional Reconstruction ◽  
Rabbit Reticulocytes

We have reconstructed the 40S ribosomal subunit at a resolution of 4 nm using the single-exposure pseudo-conical reconstruction method of Radermacher et al.Small (40S) ribosomal subunits were Isolated from rabbit reticulocytes, applied to grids and negatively stained (0.5% uranyl acetate) in a manner that “sandwiches” the specimen between two layers of carbon. Regions of the grid exhibiting uniform and thick staining were identified and photographed twice (magnification 49,000X). The first micrograph was always taken with the specimen tilted by 50° and the second was of the Identical area untilted (Fig. 1). For each of the micrographs the specimen was subjected to an electron dose of 2000-3000 el/nm2.Three hundred thirty particles appearing in the L view (defined in [4]) were selected from both tilted- and untilted-specimen micrographs. The untilted particles were aligned and their rotational alignment produced the azimuthal angles of the tilted particles in the conical tilt series.

Detection, Averaging, and 3D Reconstruction of Biological Specimens on Hypercubes (Transputer-based) Computers

1990 ◽  
Vol 48 (1) ◽  
pp. 454-455
Author(s):  
Jose-Maria Carazo ◽  
I. Benavides ◽  
S. Marco ◽  
J.L. Carrascosa ◽  
E.L. Zapata
Keyword(s):  
3D Reconstruction ◽  
3D Structure ◽  
Three Dimensional ◽  
Software Tools ◽  
Mapping Method ◽  
Computer Architectures ◽  
Parallel Computer ◽  
Reconstruction Process ◽  
Computing Power ◽  
Order Of Magnitude

Obtaining the three-dimensional (3D) structure of negatively stained biological specimens at a resolution of, typically, 2 - 4 nm is becoming a relatively common practice in an increasing number of laboratories. A combination of new conceptual approaches, new software tools, and faster computers have made this situation possible. However, all these 3D reconstruction processes are quite computer intensive, and the middle term future is full of suggestions entailing an even greater need of computing power. Up to now all published 3D reconstructions in this field have been performed on conventional (sequential) computers, but it is a fact that new parallel computer architectures represent the potential of order-of-magnitude increases in computing power and should, therefore, be considered for their possible application in the most computing intensive tasks.We have studied both shared-memory-based computer architectures, like the BBN Butterfly, and local-memory-based architectures, mainly hypercubes implemented on transputers, where we have used the algorithmic mapping method proposed by Zapata el at. In this work we have developed the basic software tools needed to obtain a 3D reconstruction from non-crystalline specimens (“single particles”) using the so-called Random Conical Tilt Series Method. We start from a pair of images presenting the same field, first tilted (by ≃55°) and then untilted. It is then assumed that we can supply the system with the image of the particle we are looking for (ideally, a 2D average from a previous study) and with a matrix describing the geometrical relationships between the tilted and untilted fields (this step is now accomplished by interactively marking a few pairs of corresponding features in the two fields). From here on the 3D reconstruction process may be run automatically.

Research on the application of 3D reconstruction technology in traditional handicraft design

2021 ◽  
pp. 002072092110052
Author(s):  
GuoLong Zhang
Keyword(s):  
Poisson Equation ◽  
Optimization Algorithm ◽  
Three Dimensional ◽  
Reconstruction Algorithm ◽  
Social Production ◽  
Design Constraint ◽  
Reconstruction Process ◽  
Key Steps ◽  
Shielding Design ◽  
Reconstruction Model

The use of computer technology for three-dimensional (3 D) reconstruction is one of the important development directions of social production. The purpose is to find a new method that can be used in traditional handicraft design, and to explore the application of 3 D reconstruction technology in it. Based on the description and analysis of 3 D reconstruction technology, the 3 D reconstruction algorithm based on Poisson equation is analyzed, and the key steps and problems of the method are clarified. Then, by introducing the shielding design constraint, a 3 D reconstruction algorithm based on shielded Poisson equation is proposed. Finally, the performance of two algorithms is compared by reconstructing the 3 D image of rabbit. The results show that: when the depth value of the algorithm is 11, the surface of the rabbit image obtained by the proposed optimization algorithm is smoother, and the details are more delicate and fluent; under different depth values, with the increase of the depth value, the number of vertices and faces of the two algorithms increase, and the optimal depth values of 3 D reconstruction are more than 8. However, the proposed optimization algorithm has more vertices, and performs better in the reconstruction process; the larger the depth value is, the more time and memory are consumed in 3 D reconstruction, so it is necessary to select the appropriate depth value; the shielding parameters of the algorithm have a great impact on the fineness of the reconstruction model. The larger the parameter is, the higher the fineness is. In a word, the proposed 3 D reconstruction algorithm based on shielded Poisson equation has better practicability and superiority.

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