Calibration approach for structured-light-stripe vision sensor based on the invariance of double cross-ratio

Wei, Zhenzhong; Zhang, Guangjun; Xu, Yuanming

doi:10.1117/1.1606683

Cited by 31 publications

(28 citation statements)

References 6 publications

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“…Our proposed method is compared with two typical calibration methods which are suited for onsite calibration, the method based on the invariance of double cross-ratio (2D target based method) [7] and the method based on 1D target [11]. As listed in Table 5, we can see that the three calibration methods have nearly the same accuracy obtained from experiments.…”

Section: The Comparison With Other Methodsmentioning

confidence: 65%

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A Sphere-Based Calibration Method for Line Structured Light Vision Sensor

Wei

Shao

Wang

et al. 2013

Advances in Mechanical Engineering

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A major difficulty in calibrating line structured light vision sensor is how to obtain enough calibration feature points, due to the fact that known world points on the calibration target do not rightly fall onto the light stripe plane. This paper presents a calibration method using a target, consisting of one sphere and a reference board, to obtain feature points on the light stripe, which is the intersection of the structured-light plane and the reference board. By moving the sphere into several positions on the fixed reference board, we can get a plane in parallel with the reference one. From the acquired right-circular cone and known radius of the sphere, the function of the reference board can be deduced. Moving the target randomly into different positions, enough points lying on the structured-light plane can be obtained. Experiment results show that the accuracy of the proposed calibration method can reach 0.102 mm within the view field of 200 mm * 200 mm; meanwhile, robustness and easy operation can be indicated.

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Section: The Comparison With Other Methodsmentioning

confidence: 65%

“…Typically, the method based on the invariance of double cross-ratio uses a planar checkerboard-pattern target to realize the calibration of the LSLVS [5][6][7]. The intersections of the light stripe plane and checkerboards with accurately known size can be obtained under the image coordinate system.…”

Section: Introductionmentioning

confidence: 99%

A Sphere-Based Calibration Method for Line Structured Light Vision Sensor

Wei

Shao

Wang

et al. 2013

Advances in Mechanical Engineering

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“…The use of structured light makes the system more reliable and the acquired data are easier to interpret. A particular technique is the laser stripe projection (Mclor, 2002;Wei et al, 2003;Zagorchev and Goshtasby, 2006). When a stripe is projected on an object, the stripe is moved in the image due to the surface variation.…”

Section: Introductionmentioning

confidence: 99%

Binocular imaging of a laser stripe and approximation networks for shape detection

Muñoz-Rodríguez

2007

Int J Imaging Syst Tech

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A technique for shape detection based on binocular imaging of a laser stripe is presented. In this technique, the object shape is recovered by means of laser stripe projection and binocular imaging. The approach of the binocular imaging in this technique is to avoid stripe occlusions, which appear due to the variation to the object surface. Based on the behavior of the stripe displacement, the object topography is computed by a Bezier approximation network. By means of this network, the measurements of the binocular geometry are avoided. The parameters of the binocular imaging are computed based on the Bezier approximation network. To reconstruct the topography, the object is scanned by a laser stripe. From the scanning, a set of binocular images of the stripe are processed to compute the object dimensions by means of the network. By applying Bezier approximation networks, the performance of the binocular imaging and the accuracy are improved. It is because the errors of the measurement are not added to the computational procedure, which performs the shape reconstruction. This procedure represents a contribution for the stripe projection methods and the binocular imaging. To describe the accuracy a root mean square of error is calculated. This technique is tested with real objects and its experimental results are presented. Also, the time processing is described. V

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“…At present, the general methods [7][8][9][10][11] are used to calibrate light plane by plane fitting after seeking the calibration points on the light plane. Considering geometric meaning of light plane, ( 1 , 2 , 3 ) indicates the normal vector of light plane, 4 represents the distance information from the origin of the coordinate system to the light plane, and then single circular target is used to complete calibration in two steps in this paper.…”

Section: Light Plane Calibrationmentioning

confidence: 99%

“…Besides, the calibration process is tedious and the accuracy is limited. On the foundation of the previous work, Huynh et al [9] and Wei et al [10] make full use of cross-ratio invariance and double cross-ratio invariance to compute calibration points, and the 2 Scientific Programming calibration accuracy is improved significantly. However, 3D precision calibration target is still employed, and calibration cost is higher all the same.…”

Section: Introductionmentioning

confidence: 99%

Field Geometric Calibration Method for Line Structured Light Sensor Using Single Circular Target

Chen

Sun

Zhang

et al. 2017

Scientific Programming

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To achieve fast calibration of line structured light sensor, a geometric calibration approach based on single circular calibration target is proposed. The proposed method uses the circular points to establish linear equations, and according to the angle constraint, the camera intrinsic parameters can be calculated through optimization. Then, the light plane calibration is accomplished in two steps. Firstly, when the vanishing lines of target plane at various postures are obtained, the intersections between vanishing lines and laser stripe can be computed, and the normal vector of light plane can be calibrated via line fitting method using intersection points. After that, the distance from the origin of camera coordinate system to the light plane can be derived based on the model of perspectivethree-point. The actual experimental result shows that this calibration method has high accuracy, its average measuring accuracy is 0.0451 mm, and relative error is 0.2314%. In addition, the entire calibration process has no complex operations. It is simple, convenient, and suitable for calibration on sites.

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Calibration approach for structured-light-stripe vision sensor based on the invariance of double cross-ratio

Cited by 31 publications

References 6 publications

A Sphere-Based Calibration Method for Line Structured Light Vision Sensor

A Sphere-Based Calibration Method for Line Structured Light Vision Sensor

Binocular imaging of a laser stripe and approximation networks for shape detection

Field Geometric Calibration Method for Line Structured Light Sensor Using Single Circular Target

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