Accurate All-Round 3D Measurement Using Trinocular Spherical Stereo via Weighted Reprojection Error Minimization

2019 ◽  
Author(s):  
Wanqi Yin ◽  
Sarthak Pathak ◽  
Alessandro Moro ◽  
Atsushi Yamashita ◽  
Hajime Asama
Keyword(s):  
Error Minimization ◽  
3D Measurement ◽  
Reprojection Error

scholarly journals Methods for Simultaneous Robot-World-Hand–Eye Calibration: A Comparative Study

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2837 ◽  
Author(s):  
Ali ◽  
Suominen ◽  
Gotchev ◽  
Morales
Keyword(s):  
Comparative Analysis ◽  
Minimization Problem ◽  
State Of The Art ◽  
Simulated Data ◽  
Error Modeling ◽  
Robotic Arm ◽  
Error Minimization ◽  
Calibration Problem ◽  
Reprojection Error ◽  
Art Methods

In this paper, we propose two novel methods for robot-world-hand–eye calibration and provide a comparative analysis against six state-of-the-art methods. We examine the calibration problem from two alternative geometrical interpretations, called 'hand–eye' and 'robot-world-hand–eye', respectively. The study analyses the effects of specifying the objective function as pose error or reprojection error minimization problem. We provide three real and three simulated datasets with rendered images as part of the study. In addition, we propose a robotic arm error modeling approach to be used along with the simulated datasets for generating a realistic response. The tests on simulated data are performed in both ideal cases and with pseudo-realistic robotic arm pose and visual noise. Our methods show significant improvement and robustness on many metrics in various scenarios compared to state-of-the-art methods.

scholarly journals Methods for Simultaneous Robot-World Hand-Eye Calibration: A Comparative Study

2019 ◽  
Author(s):  
Ihtisham Ali ◽  
Olli Suominen ◽  
Atanas Gotchev ◽  
Emilio Ruiz Morales
Keyword(s):  
Comparative Analysis ◽  
Minimization Problem ◽  
State Of The Art ◽  
Simulated Data ◽  
Error Modeling ◽  
Robotic Arm ◽  
Error Minimization ◽  
Calibration Problem ◽  
Reprojection Error ◽  
Art Methods

In this paper, we propose two novel methods for robot-world/hand-eye calibration and provide a comparative analysis against six state-of-the-art methods. We examine the calibration problem from two alternative geometrical interpretations, called hand-eye and robot-world-hand-eye, respectively. The study analyses the effects of specifying the objective function as pose error or reprojection error minimization problem. We provide three real and three simulated datasets with rendered images as part of the study. In addition, we propose a robotic arm error modeling approach to be used along with the simulated datasets for generating a realistic response. The tests on simulated data are performed in both ideal cases and with pseudo-realistic robotic arm pose and visual noise. Our methods show significant improvement and robustness on many metrics in various scenarios compared to state-of-the-art methods.

Counterfeit Parts Recognition and Detection for Failure Analysts

2010 ◽  
Author(s):  
Katherine V. Whittington
Keyword(s):  
Thermal Cycle ◽  
Visual Inspection ◽  
Acoustic Microscopy ◽  
Scanning Acoustic Microscopy ◽  
3D Measurement ◽  
X Ray ◽  
Wide Range ◽  
Electronic Parts ◽  
Testing Awareness

Abstract The electronics supply chain is being increasingly infiltrated by non-authentic, counterfeit electronic parts, whose use poses a great risk to the integrity and quality of critical hardware. There is a wide range of counterfeit parts such as leads and body molds. The failure analyst has many tools that can be used to investigate counterfeit parts. The key is to follow an investigative path that makes sense for each scenario. External visual inspection is called for whenever the source of supply is questionable. Other methods include use of solvents, 3D measurement, X-ray fluorescence, C-mode scanning acoustic microscopy, thermal cycle testing, burn-in technique, and electrical testing. Awareness, vigilance, and effective investigations are the best defense against the threat of counterfeit parts.

Automated 3D measurement of fiber cross section morphology in handsheets

2012 ◽  
Vol 27 (2) ◽  
pp. 264-269 ◽  
Author(s):  
Christian Lorbach ◽  
Ulrich Hirn ◽  
Johannes Kritzinger ◽  
Wolfgang Bauer
Keyword(s):  
Image Analysis ◽  
Cross Section ◽  
Cross Sections ◽  
Image Plane ◽  
3D Measurement ◽  
Cross Sectional ◽  
Fiber Cross Section ◽  
Fiber Wall ◽  
Sectional Shape ◽  
Cross Section Geometry

Abstract We present a method for 3D measurement of fiber cross sectional morphology from handsheets. An automated procedure is used to acquire 3D datasets of fiber cross sectional images using an automated microtome and light microscopy. The fiber cross section geometry is extracted using digital image analysis. Simple sample preparation and highly automated image acquisition and image analysis are providing an efficient tool to analyze large samples. It is demonstrated that if fibers are tilted towards the image plane the images of fiber cross sections are always larger than the true fiber cross section geometry. In our analysis the tilting angles of the fibers to the image plane are measured. The resulting fiber cross sectional images are distorted to compensate the error due to fiber tilt, restoring the true fiber cross sectional shape. We use an approximated correction, the paper provides error estimates of the approximation. Measurement results for fiber wall thickness, fiber coarseness and fiber collapse are presented for one hardwood and one softwood pulp.

scholarly journals Orientation-Constrained System for Lamp Detection in Buildings Based on Computer Vision

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1516 ◽  
Author(s):  
Francisco Troncoso-Pastoriza ◽  
Pablo Eguía-Oller ◽  
Rebeca Díaz-Redondo ◽  
Enrique Granada-Álvarez ◽  
Aitor Erkoreka
Keyword(s):  
Computer Vision ◽  
Optimization Methods ◽  
Geometric Information ◽  
Constrained System ◽  
Building Information Modelling ◽  
Correct Model ◽  
Reprojection Error ◽  
Localization Errors ◽  
Building Information ◽  
Error Filtering

Computer vision is used in this work to detect lighting elements in buildings with the goal of improving the accuracy of previous methods to provide a precise inventory of the location and state of lamps. Using the framework developed in our previous works, we introduce two new modifications to enhance the system: first, a constraint on the orientation of the detected poses in the optimization methods for both the initial and the refined estimates based on the geometric information of the building information modelling (BIM) model; second, an additional reprojection error filtering step to discard the erroneous poses introduced with the orientation restrictions, keeping the identification and localization errors low while greatly increasing the number of detections. These enhancements are tested in five different case studies with more than 30,000 images, with results showing improvements in the number of detections, the percentage of correct model and state identifications, and the distance between detections and reference positions.

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