Semi-automatic calibration of a projector-camera system using arbitrary objects with known geometry

Author(s):  
Christoph Resch ◽  
Peter Keitler ◽  
Christoffer Menk ◽  
Gudrun Klinker
2015 ◽  
Vol 21 (11) ◽  
pp. 1211-1220 ◽  
Author(s):  
Christoph Resch ◽  
Hemal Naik ◽  
Peter Keitler ◽  
Steven Benkhardt ◽  
Gudrun Klinker

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7107
Author(s):  
Livio Bisogni ◽  
Ramtin Mollaiyan ◽  
Matteo Pettinari ◽  
Paolo Neri ◽  
Marco Gabiccini

Rotary tables are often used to speed up the acquisition time during the 3D scanning of complex geometries. In order to avoid manual registration of the point clouds acquired with different orientations, automatic algorithms to compensate the rotation were developed. Alternatively, a proper calibration of the rotary axis with respect to the camera system is needed. Several methods are available in the literature, but they only consider a single-axis calibration. In this paper, a method for the simultaneous calibration of both axes of the table is proposed. A checkerboard is attached to the table, and several images with different poses are acquired. An optimization algorithm is then setup to determine the orientation and the locations of the two axes. A metric to assess the calibration quality was also defined by computing the average mean reprojection error. This metric is used to investigate the optimal number and distribution of the calibration poses, demonstrating that the optimum calibration results are achieved when a wider dispersion of the calibration poses is adopted.


Author(s):  
Haixia Wang ◽  
Xiao Lu ◽  
Zhanyi Hu ◽  
Yuxia Li

Purpose – The purpose of this paper is to present a fully automatic calibration method for hand-eye serial robot system is presented in this paper. The so-called “fully automatic” is meant to calibrate the robot body, the hand-eye relation, and the used measuring binocular system at the same time. Design/methodology/approach – The calibration is done by controlling the joints to rotate several times one by one in the reverse order (i.e. from the last one to the first one), and simultaneously take pictures of the checkerboard patterns by the stereo camera system attached on the end-effector, then the whole robot system can be calibrated automatically from these captured images. In addition, a nonlinear optimization step is used to further refine the calibration results. Findings – The proposed method is essentially based on an improved screw axis identification method, and it needs only a mirror and some paper checkerboard patterns without resorting to any additional costly measuring instrument. Originality/value – Simulations and real experiments on MOTOMAN-UP6 robot system demonstrate the feasibility and effectiveness of the proposed method.


2011 ◽  
Vol 58-60 ◽  
pp. 2308-2313
Author(s):  
Tao Yang ◽  
Yue Liu ◽  
You Lu

A precise, fast, and fully automatic calibration method is proposed to address the shortcomings in currently used large-scale interactive camera-projector systems. These shortcomings include a small number of calibration points used in manual calibration, large errors, huge time consumption, and lack of professional quality operations. The proposed method applies mechanical wavelength switching in the projected image to capture multi-regional vertices. The co-linearity of each point in the projected images is calculated to determine the actual location of the interactive points in the projected image. The point-by-point computation adopted in the method promotes the automatic elimination of uncorrectable systematic errors in large-scale optical devices. The automatic error elimination not only increases the accuracy of the interactive system and reduces the complexity of system installation, but also increases the flexibility of the interactive system.


Author(s):  
M. Hardner ◽  
D. Schneider

Abstract. Cameras can provide accurate 3D positioning for a robotic system. Calibration of interior orientation as well as the relative orientation when using multiple cameras is a necessary step. Integration of the automatic calibration process into the robot system is useful to provide a simple system for the user. The paper presents a method for calibrating a multi camera system using the open source Ceres solver and compares it to a commercial software. The motivation is a measurement system for laboratory automation where biological samples in Petri dishes will be manipulated with different tools. For this application we will examine the camera setup, show first results of the calibration and the possible accuracy. Lastly we will draw conclusions for the final system prototype and necessary improvements to be implemented in order to provide accurate measurements.


2013 ◽  
Vol 20 (2) ◽  
pp. 229-238 ◽  
Author(s):  
Paweł Peczyński ◽  
Bartosz Ostrowski

Abstract The article describes a technique developed for identification of extrinsic parameters of a stereovision camera system for the purpose of image rectification without the use of reference calibration objects. The goal of the presented algorithm is the determination of the mutual position of cameras, under the assumption that they can be modeled by pinhole cameras, are separated by a fixed distance and are moving through a stationary scene. The developed method was verified experimentally on image sequences of a scene with a known structure.


Author(s):  
W.J. de Ruijter ◽  
Sharma Renu

Established methods for measurement of lattice spacings and angles of crystalline materials include x-ray diffraction, microdiffraction and HREM imaging. Structural information from HREM images is normally obtained off-line with the traveling table microscope or by the optical diffractogram technique. We present a new method for precise measurement of lattice vectors from HREM images using an on-line computer connected to the electron microscope. It has already been established that an image of crystalline material can be represented by a finite number of sinusoids. The amplitude and the phase of these sinusoids are affected by the microscope transfer characteristics, which are strongly influenced by the settings of defocus, astigmatism and beam alignment. However, the frequency of each sinusoid is solely a function of overall magnification and periodicities present in the specimen. After proper calibration of the overall magnification, lattice vectors can be measured unambiguously from HREM images.Measurement of lattice vectors is a statistical parameter estimation problem which is similar to amplitude, phase and frequency estimation of sinusoids in 1-dimensional signals as encountered, for example, in radar, sonar and telecommunications. It is important to properly model the observations, the systematic errors and the non-systematic errors. The observations are modelled as a sum of (2-dimensional) sinusoids. In the present study the components of the frequency vector of the sinusoids are the only parameters of interest. Non-systematic errors in recorded electron images are described as white Gaussian noise. The most important systematic error is geometric distortion. Lattice vectors are measured using a two step procedure. First a coarse search is obtained using a Fast Fourier Transform on an image section of interest. Prior to Fourier transformation the image section is multiplied with a window, which gradually falls off to zero at the edges. The user indicates interactively the periodicities of interest by selecting spots in the digital diffractogram. A fine search for each selected frequency is implemented using a bilinear interpolation, which is dependent on the window function. It is possible to refine the estimation even further using a non-linear least squares estimation. The first two steps provide the proper starting values for the numerical minimization (e.g. Gauss-Newton). This third step increases the precision with 30% to the highest theoretically attainable (Cramer and Rao Lower Bound). In the present studies we use a Gatan 622 TV camera attached to the JEM 4000EX electron microscope. Image analysis is implemented on a Micro VAX II computer equipped with a powerful array processor and real time image processing hardware. The typical precision, as defined by the standard deviation of the distribution of measurement errors, is found to be <0.003Å measured on single crystal silicon and <0.02Å measured on small (10-30Å) specimen areas. These values are ×10 times larger than predicted by theory. Furthermore, the measured precision is observed to be independent on signal-to-noise ratio (determined by the number of averaged TV frames). Obviously, the precision is restricted by geometric distortion mainly caused by the TV camera. For this reason, we are replacing the Gatan 622 TV camera with a modern high-grade CCD-based camera system. Such a system not only has negligible geometric distortion, but also high dynamic range (>10,000) and high resolution (1024x1024 pixels). The geometric distortion of the projector lenses can be measured, and corrected through re-sampling of the digitized image.


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