High Precision Laser Scanning of Metallic Surfaces

Amir, Yousaf Muhammad; Thörnberg, Benny

doi:10.1155/2017/4134205

Cited by 27 publications

(10 citation statements)

References 26 publications

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“…or to the nature of the scanned objects themselves. For instance, the scanning process of objects presenting shiny metallic areas could easily lead to an incomplete or noisy 3D surface [8] . Furthermore, many times the acquired scene is complex and contains several elements which are to be filtered out as they are not relevant for the subsequent analysis.…”

Section: Introductionmentioning

confidence: 99%

Cylinders extraction in non-oriented point clouds as a clustering problem

Bergamasco

Pistellato

Albarelli

et al. 2020

Pattern Recognition

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Finding geometric primitives in 3D point clouds is a fundamental task in many engineering applications such as robotics, autonomous-vehicles and automated industrial inspection. Among all solid shapes, cylinders are frequently found in a variety of scenes, comprising natural or man-made objects. Despite their ubiquitous presence, automated extraction and fitting can become challenging if performed "in-the-wild", when the number of primitives is unknown or the point cloud is noisy and not oriented.In this paper we pose the problem of extracting multiple cylinders in a scene by means of a Game-Theoretic inlier selection process exploiting the geometrical relations between pairs of axis candidates. First, we formulate the similarity between two possible cylinders considering the rigid motion aligning the two axes to the same line. This motion is represented with a unitary dual-quaternion so that the distance between two cylinders is induced by the length of the shortest geodesic path in SE(3). Then, a Game-Theoretical process exploits such similarity function to extract sets of primitives maximizing their inner mutual consensus. The outcome of the evolutionary process consists in a probability distribution over the sets of candidates (ie axes), which in turn is used to directly estimate the final cylinder parameters. An extensive experimental section shows that the proposed algorithm offers a high resilience to noise, since the process inherently discards inconsistent data. Compared to other methods, it does not need point normals and does not require a fine tuning of multiple parameters.

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Section: Introductionmentioning

confidence: 99%

Cylinders extraction in non-oriented point clouds as a clustering problem

Bergamasco

Pistellato

Albarelli

et al. 2020

Pattern Recognition

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show abstract

“…For metallic surface, there is some noise left in the sub-model when there are some holes or bosses. Spurious reflection and scattering in metallic surfaces generate some noise points close to the model [20]. The outliers caused by the internal holes were removed by the region growing algorithm [21].…”

Section: Experiments and Resultsmentioning

confidence: 99%

An Improved Low-Noise Processing Methodology Combined with PCL for Industry Inspection Based on Laser Line Scanner

Zhou

et al. 2019

Sensors

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This paper introduces a three-dimensional (3D) point cloud data obtained method based on a laser line scanner and data processing technology via a PCL open project. This paper also provides a systematical analysis of the error types of laser line scanner and common error reducing solutions and calibration of the laser line scanner. The laser line scanner is combined with a precision motorized stage to obtain the 3D information of a measurand, and the format of point cloud data is converted via the set of x, y, and z coordinates. The original signal is processed according to the noise signal types of the raw point cloud data. This paper introduced a denoise process step by step combining various segmentation methods and a more optimized three-dimensional data model is obtained. A novel method for industry inspection based on the numerous point cloud for the dimensions evaluation via feature extraction and the deviation of complex surface between scanned point cloud and designed point cloud via registration algorithm is proposed. Measurement results demonstrate the good performance of the proposed methods. An obtained point cloud precision of ±10 μm is achieved, and the precision of dimension evaluation is less than ±40 μm. The results shown in the research demonstrated that the proposed method allows a higher precision and relative efficiency in measurement of dimensions and deviation of complex surfaces in industrial inspection.

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“…Miesen et al [35] investigated an inspection process using a point laser displacement system. Amir and Thörnberg [36] researched various image processing techniques with the objective of reducing disturbances within LLSS image data. For this purpose they examined the influences of noise, dynamics in light intensity, and surface scattering on the example of metallic surface inspection.…”

Section: Data Recording and Inspection Systemsmentioning

confidence: 99%

Imaging sensor data modelling and evaluation based on optical composite characteristics

Meister

Grundhöfer

Stüve

et al. 2021

Int J Adv Manuf Technol

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Automated Fibre Placement is a common manufacturing technique for composite parts in the aero-space industry. Therefore, a visual part inspection is required which often covers up to 50% of the actual production time. Moreover, the inspection quality of this manual step fluctuates significantly. A camera-based automated inline inspection is capable of increasing the inspection efficiency and accuracy. However, the interpretability of the acquired data strongly depends on the sensor configuration and the inspected material. Thus, this paper introduces methods for modelling and assessing an imaging sensor on the example of a composite material reflecting a spot laser to a camera sensor. In this context, the reflection properties of the material are incorporated into a simulation and validated in comparison to real camera images from the experimental setup. The EMVA 1288 sensor model in combination with the Cramér–Rao lower bound indicates a feasible estimability of the beam propagation, but shows limitations in the predictability of the number of incident photons. The laser spot analysis indicated that the laser spot can deviate from an exact oval shape but its peak value is suitable for robust spot identification in an image. The outlined methodology is also adaptable to other imaging sensors, illumination sources and materials. Thus, the findings can be useful for other fields and manufacturing processes.

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High Precision Laser Scanning of Metallic Surfaces

Cited by 27 publications

References 26 publications

Cylinders extraction in non-oriented point clouds as a clustering problem

Cylinders extraction in non-oriented point clouds as a clustering problem

An Improved Low-Noise Processing Methodology Combined with PCL for Industry Inspection Based on Laser Line Scanner

Imaging sensor data modelling and evaluation based on optical composite characteristics

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