scholarly journals A Range-Independent Disparity-Based Calibration Model for Structured Light Pattern-Based RGBD Sensor

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 639 ◽  
Author(s):  
Wenbin Li ◽  
Yaxin Li ◽  
Walid Darwish ◽  
Shengjun Tang ◽  
Yuling Hu ◽  
...  
Keyword(s):  
Structured Light ◽  
Full Range ◽  
Infrared Camera ◽  
Calibration Method ◽  
Depth Information ◽  
Calibration Model ◽  
Ir Camera ◽  
Depth Measurement ◽  
Light Pattern ◽  
Calibration Models

Consumer-grade RGBD sensors that provide both colour and depth information have many potential applications, such as robotics control, localization, and mapping, due to their low cost and simple operation. However, the depth measurement provided by consumer-grade RGBD sensors is still inadequate for many high-precision applications, such as rich 3D reconstruction, accurate object recognition and precise localization, due to the fact that the systematic errors of RGB sensors increase exponentially with the ranging distance. Most existing calibration models for depth measurement must be carried out with different distances. In this paper, we reveal the mechanism of how an infrared (IR) camera and IR projector contribute to the overall non-centrosymmetric distortion of a structured light pattern-based RGBD sensor. Then, a new two-step calibration method for RGBD sensors based on the disparity measurement is proposed, which is range-independent and has full frame coverage. Three independent calibration models are used for the calibration for the three main components of the RGBD sensor errors: the infrared camera distortion, the infrared projection distortion, and the infrared cone-caused bias. Experiments show the proposed calibration method can provide precise calibration results in full-range and full-frame coverage of depth measurement. The offset in the edge area of long-range depth (8 m) is reduced from 86 cm to 30 cm, and the relative error is reduced from 11% to 3% of the range distance. Overall, at far range the proposed calibration method can improve the depth accuracy by 70% in the central region of depth frame and 65% in the edge region.

scholarly journals A Spliced Satellite Optical Camera Geometric Calibration Method Based on Inter-Chip Geometry Constraints

2021 ◽  
Vol 13 (14) ◽  
pp. 2832
Author(s):  
Tao Wang ◽  
Yan Zhang ◽  
Yongsheng Zhang ◽  
Zhenchao Zhang ◽  
Xiongwu Xiao ◽  
...  
Keyword(s):  
Satellite Images ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Calibration Model ◽  
Geometric Calibration ◽  
Sensing Technology ◽  
Calibration Models ◽  
Major Bottleneck ◽  
Chip Geometry ◽  
Calibration Parameters

When in orbit, spliced satellite optical cameras are affected by various factors that degrade the actual image stitching precision and the accuracy of their data products. This is a major bottleneck in the current remote sensing technology. Previous geometric calibration research has mostly focused on stitched satellite images and has largely ignored the inter-chip relationship among original multi-chip images, resulting in accuracy loss in geometric calibration and subsequent image products. Therefore, in this paper, a novel geometric calibration method is proposed for spliced satellite optical cameras. The integral geometric calibration model was developed on inter-chip geometry constraints among multi-chip images, including the corresponding external and internal calibration models. The proposed approach improves uncontrolled geopositioning accuracy and enhances mosaic precision at the same time. For evaluation, images from the optical butting satellite ZiYuan-3 (ZY-3) and mechanical interleaving satellite Tianhui-1 (TH-1) were used for the experiments. Multiple sets of satellite data of the Songshan Calibration field and other regions were used to evaluate the reliability, stability, and applicability of the calibration parameters. The experiment results found that the proposed method obtains reliable camera alignment angles and interior calibration parameters and generates high-precision seamless mosaic images. The calibration scheme is not only suitable for mechanical interleaving cameras with large geometric displacement among multi-chip images but is also effective for optical butting cameras with minor chip offset. It also significantly improves uncontrolled geopositioning accuracy for both types of spliced satellite images. Moreover, the proposed calibration procedure results in multi-chip satellite images being seamlessly stitched together and mosaic errors within one pixel.

A Depth Measurement Method Using Two Structured Light Binary Patterns

2013 ◽  
Vol 397-400 ◽  
pp. 1709-1712
Author(s):  
Wan Zhen Zhang ◽  
Peng Cheng Yang ◽  
Zi Ming Guo ◽  
Guo Hao Ju ◽  
Bin Lin
Keyword(s):  
Phase Retrieval ◽  
Pulse Width Modulation ◽  
Structured Light ◽  
Measurement Range ◽  
Modulation Method ◽  
Composite Image ◽  
Linear Effect ◽  
Depth Measurement ◽  
Light Pattern ◽  
Depth Reconstruction

An improved tripolar pulse width modulation method has been proposed in this paper. According to the linear effect of optical system defocusing, the three-gray-level structured light pattern can be split into two binary ones. With the composite image, the same measurement result as the tripolar method is obtained. Simulation result shows that, under three-step phase shifting method, the error of phase retrieval is greatly eliminated. Thus, the proposed method can achieve better depth reconstruction results than PWM method. Furthermore, both simulation and experimental results show that the measurement range of this method is effectively extended.

Temporal Matrices Mapping-Based Calibration Method for Event-Driven Structured Light Systems

2021 ◽  
Vol 21 (2) ◽  
pp. 1799-1808
Author(s):  
Guijin Wang ◽  
Chenchen Feng ◽  
Xiaowei Hu ◽  
Huazhong Yang
Keyword(s):  
Structured Light ◽  
Calibration Method ◽  
Event Driven ◽  
Structured Light Systems

Characterization of Fouled Flat Sheet Membranes by Infrared Thermography

2014 ◽  
Author(s):  
Kennethrex O. Ndukaife ◽  
George Agbai Nnanna
Keyword(s):  
Surface Temperature ◽  
Infrared Thermography ◽  
Spectral Power ◽  
Membrane Surface ◽  
Infrared Camera ◽  
Feed Solution ◽  
Feed Concentration ◽  
Ir Camera ◽  
Measure Surface Temperature

An Infrared thermography (IRT) technique for characterization of fouling on membrane surface has been developed. The emitted spectral power from the fouled membrane is a function of emissivity and surface morphology. In this work, a FLIR A320 IR camera was used to measure surface temperature and emissivity. The surface temperature and the corresponding emissivity value of various areas on the fouled membrane surface is measured by the infrared camera and recorded alongside its thermogram. Different fouling experiments were performed using different concentrations of aluminum oxide nanoparticle mixed with deionized water as feed solution (333 ppm, 1833 ppm and 3333 ppm) so as to investigate the effect of feed concentration on the degree of fouling and thus its effect on the emissivity values measured on the membrane surfaces. Surface plots in 3D and Line plots are obtained for the measured emissivity values and thickness of the fouling deposit on the membrane surface respectively. The results indicate that the IRT technique is sensitive to changes that occur on the membrane surface due to deposition of contaminants on the membrane surface and that emissivity is a function of temperature, surface roughness and thickness of the specimen under investigation.

scholarly journals Thermal Modeling and Calibration Method in Complex Temperature Field for Single-Axis Rotational Inertial Navigation System

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 384 ◽  
Author(s):  
Zihui Wang ◽  
Xianghong Cheng ◽  
Jingjing Du
Keyword(s):  
Temperature Field ◽  
Inertial Navigation ◽  
Calibration Method ◽  
Measurement Unit ◽  
Calibration Model ◽  
Navigation Systems ◽  
Moving Vehicle ◽  
Temperature Change Rate ◽  
Environment Temperature ◽  
Complex Temperature

Single-axis rotational inertial navigation systems (single-axis RINSs) are widely used in high-accuracy navigation because of their ability to restrain the horizontal axis errors of the inertial measurement unit (IMU). The IMU errors, especially the biases, should be constant during each rotation cycle that is to be modulated and restrained. However, the temperature field, consisting of the environment temperature and the power heating of single-axis RINS, affects the IMU performance and changes the biases over time. To improve the precision of single-axis RINS, the change of IMU biases caused by the temperature should be calibrated accurately. The traditional thermal calibration model consists of the temperature and temperature change rate, which does not reflect the complex temperature field of single-axis RINS. This paper proposed a multiple regression method with a temperature gradient in the model, and in order to describe the complex temperature field thoroughly, a BP neural network method is proposed with consideration of the coupled items of the temperature variables. Experiments show that the proposed methods outperform the traditional calibration method. The navigation accuracy of single-axis RINS can be improved by up to 47.41% in lab conditions and 65.11% in the moving vehicle experiment, respectively.

scholarly journals On-Orbit Geometric Calibration from the Relative Motion of Stars for Geostationary Cameras

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6668
Author(s):  
Linyi Jiang ◽  
Xiaoyan Li ◽  
Liyuan Li ◽  
Lin Yang ◽  
Lan Yang ◽  
...  
Keyword(s):  
Relative Motion ◽  
Calibration Method ◽  
System Structure ◽  
Calibration Model ◽  
Control Points ◽  
Penetration Process ◽  
Geometric Calibration ◽  
Positioning Errors ◽  
Ground Control Points ◽  
Motion Transformation

Affected by the vibrations and thermal shocks during launch and the orbit penetration process, the geometric positioning model of the remote sensing cameras measured on the ground will generate a displacement, affecting the geometric accuracy of imagery and requiring recalibration. Conventional methods adopt the ground control points (GCPs) or stars as references for on-orbit geometric calibration. However, inescapable cloud coverage and discontented extraction algorithms make it extremely difficult to collect sufficient high-precision GCPs for modifying the misalignment of the camera, especially for geostationary satellites. Additionally, the number of the observed stars is very likely to be inadequate for calibrating the relative installations of the camera. In terms of the problems above, we propose a novel on-orbit geometric calibration method using the relative motion of stars for geostationary cameras. First, a geometric calibration model is constructed based on the optical system structure. Then, we analyze the relative motion transformation of the observed stars. The stellar trajectory and the auxiliary ephemeris are used to obtain the corresponding object vector for correcting the associated calibration parameters iteratively. Experimental results evaluated on the data of a geostationary experiment satellite demonstrate that the positioning errors corrected by this proposed method can be within ±2.35 pixels. This approach is able to effectively calibrate the camera and improve the positioning accuracy, which avoids the influence of cloud cover and overcomes the great dependence on the number of the observed stars.

scholarly journals ENHANCED RGB-D MAPPING METHOD FOR DETAILED 3D MODELING OF LARGE INDOOR ENVIRONMENTS

2016 ◽  
Vol III-1 ◽  
pp. 151-158
Author(s):  
Shengjun Tang ◽  
Qing Zhu ◽  
Wu Chen ◽  
Walid Darwish ◽  
Bo Wu ◽  
...  
Keyword(s):  
3D Modeling ◽  
Visual Information ◽  
3D Models ◽  
Measurement Range ◽  
Mapping Method ◽  
Depth Information ◽  
Indoor Environments ◽  
Recovery Method ◽  
Depth Measurement ◽  
Rgb Image

RGB-D sensors are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks with respect to 3D dense mapping of indoor environments. First, they only allow a measurement range with a limited distance (e.g., within 3 m) and a limited field of view. Second, the error of the depth measurement increases with increasing distance to the sensor. In this paper, we propose an enhanced RGB-D mapping method for detailed 3D modeling of large indoor environments by combining RGB image-based modeling and depth-based modeling. The scale ambiguity problem during the pose estimation with RGB image sequences can be resolved by integrating the information from the depth and visual information provided by the proposed system. A robust rigid-transformation recovery method is developed to register the RGB image-based and depth-based 3D models together. The proposed method is examined with two datasets collected in indoor environments for which the experimental results demonstrate the feasibility and robustness of the proposed method

scholarly journals Laser Distance Sensors Evaluation for Geomatics Researches

2020 ◽  
pp. 1831
Author(s):  
Abbas Zedan Khalaf ◽  
Bashar H Alyasery
Keyword(s):  
Reference Values ◽  
3D Modeling ◽  
Full Range ◽  
Calibration Method ◽  
Additive Error ◽  
Statistical Indicator ◽  
Laser Distance Sensor ◽  
Left And Right ◽  
Distance Sensor

In this study, an approach inspired by a standardized calibration method was used to test a laser distance meter (LDM). A laser distance sensor (LDS) was tested with respect to an LDM and then a statistical indicator explained that the former functions in a similar manner as the latter. Also, regression terms were used to estimate the additive error and scale the correction of the sensors. The specified distance was divided into several parts with percent of longest one and observed using two sensors, left and right. These sensors were evaluated by using the regression between the measured and the reference values. The results were computed using MINITAB 17 package software and excel office package. The accuracy of the results in this work was ± 4.4mm + 50.89 ppm and ± 4.96mm + 99.88 ppm for LDS1 and LDS2, respectively, depending on the LDM accuracy which was computed to the full range (100 m). Using these sensors can be very effective for industrial, 3D modeling purposes, and many other applications, especially that it is inexpensive and available in many versions.

scholarly journals Calibration Method for Line-Structured Light Three-Dimensional Measurements Based on a Single Circular Target

2022 ◽  
Vol 12 (2) ◽  
pp. 588
Author(s):  
Jun Wang ◽  
Xuexing Li
Keyword(s):  
Structured Light ◽  
Three Dimensional ◽  
Calibration Method ◽  
Optical Center ◽  
3D Measurements ◽  
Light Plane ◽  
Laser Projector ◽  
Dimensional Measurements ◽  
Intersection Points ◽  
Circular Target

Single circular targets are widely used as calibration objects during line-structured light three-dimensional (3D) measurements because they are versatile and easy to manufacture. This paper proposes a new calibration method for line-structured light 3D measurements based on a single circular target. First, the target is placed in several positions and illuminated by a light beam emitted from a laser projector. A camera captures the resulting images and extracts an elliptic fitting profile of the target and the laser stripe. Second, an elliptical cone equation defined by the elliptic fitting profile and optical center of the camera is established based on the projective geometry. By combining the obtained elliptical cone and the known diameter of the circular target, two possible positions and orientations of the circular target are determined and two groups of 3D intersection points between the light plane and the circular target are identified. Finally, the correct group of 3D intersection points is filtered and the light plane is progressively fitted. The accuracy and effectiveness of the proposed method are verified both theoretically and experimentally. The obtained results indicate that a calibration accuracy of 0.05 mm can be achieved for an 80 mm × 80 mm planar target.

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