On-Line Laser Triangulation Scanner for Wood Logs Surface Geometry Measurement

Siekański, Piotr; Magda, Krzysztof; Malowany, Krzysztof; Rutkiewicz, Jan; Styk, Adam; Krzesłowski, Jakub; Kowaluk, Tomasz; Zagórski, A.

doi:10.3390/s19051074

Cited by 23 publications

(11 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It was a very popular solution for the size sorting of logs supplied to the sawmill. However, nowadays it is replaced by the 3D laser triangulation systems relying on the image analysis of the structured light profiles (usually laser) that appear as deformed when observed from an angle (Siekański et al 2019). The advanced analysis of the surface texture allows identification of some wood defects appearing as particular textures of the bark.…”

Section: Sensors For Timber Quality Assessmentmentioning

confidence: 99%

Smart Harvest Operations and Timber Processing for Improved Forest Management

Picchi

Sandak²,

Grigolato

et al. 2021

Managing Forest Ecosystems

View full text Add to dashboard Cite

Climate-smart forestry can be regarded as the evolution of traditional silviculture. As such, it must rely on smart harvesting equipment and techniques for a reliable and effective application. The introduction of sensors and digital information technologies in forest inventories, operation planning, and work execution enables the achievement of the desired results and provides a range of additional opportunities and data. The latter may help to better understand the results of management options on forest health, timber quality, and many other applications. The introduction of intelligent forest machines may multiply the beneficial effect of digital data gathered for forest monitoring and management, resulting in forest harvesting operations being more sustainable in terms of costs and environment. The interaction can be pushed even further by including the timber processing industry, which assesses physical and chemical characteristics of wood with sensors to optimize the transformation process. With the support of an item-level traceability system, the same data could provide a formidable contribution to CSF. The “memory” of wood could support scientists to understand the response of trees to climate-induced stresses and to design accordingly an adaptive silviculture, contributing to forest resilience in the face of future changes due to human-induced climate alteration.

show abstract

Section: Sensors For Timber Quality Assessmentmentioning

confidence: 99%

Smart Harvest Operations and Timber Processing for Improved Forest Management

Picchi

Sandak²,

Grigolato

et al. 2021

Managing Forest Ecosystems

View full text Add to dashboard Cite

show abstract

“…The scanControl 2900–25/BL blue light laser profile sensor had a resolution of 2 μm and a scanner sampling frequency of 300 Hz. The non-contact sensor used the triangulation method, which is commonly used to examine the shape of objects [ 36 , 37 , 38 , 39 ]. The blue light sensor used a laser diode with a wavelength of 405 nm and was suitable for transparent, semitransparent, and organic materials.…”

Section: Development Of a 3d Scanning System For The Imaging Of Tementioning

confidence: 99%

A 3D Scanning System for Inverse Analysis of Moist Biological Samples: Design and Validation Using Tendon Fascicle Bundles

Dąbrowska

Ekiert

Wójcik

et al. 2020

Sensors

View full text Add to dashboard Cite

In this article, we present the design and validation of a non-contact scanning system for the development of a three-dimensional (3D) model of moist biological samples. Due to the irregular shapes and low stiffness of soft tissue samples, the use of a non-contact, reliable geometry scanning system with good accuracy and repeatability is required. We propose a reliable 3D scanning system consisting of a blue light profile sensor, stationary and rotating frames with stepper motors, gears and a five-phase stepping motor unit, single-axis robot, control system, and replaceable sample grips, which once mounted onto the sample, are used for both scanning and mechanical tests. The proposed system was validated by comparison of the cross-sectional areas calculated based on 3D models, digital caliper, and vision-based methods. Validation was done on regularly-shaped samples, a wooden twig, as well as tendon fascicle bundles. The 3D profiles were used for the development of the 3D computational model of the sample, including surface concavities. Our system allowed for 3D model development of samples with a relative error of less than 1.2% and high repeatability in approximately three minutes. This was crucial for the extraction of the mechanical properties and subsequent inverse analysis, enabling the calibration of complex material models.

show abstract

“…Today, many application fields require technology for 3D modeling of real-world objects, such as design and construction of augmented reality (AR), quality verification, the restoration of lost CAD data, heritage scanning, surface deformation tracking, 3D reconstruction for object recognition and so on [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ]. Among the non-contact scanning methods, the method using a camera and a line laser is widely used because the scanning speed is relatively fast and there is no damage to the object [ 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

Development of a Wide Area 3D Scanning System with a Rotating Line Laser

Lee

Shin

Lee

2021

Sensors

View full text Add to dashboard Cite

In a 3D scanning system, using a camera and a line laser, it is critical to obtain the exact geometrical relationship between the camera and laser for precise 3D reconstruction. With existing depth cameras, it is difficult to scan a large object or multiple objects in a wide area because only a limited area can be scanned at a time. We developed a 3D scanning system with a rotating line laser and wide-angle camera for large-area reconstruction. To obtain 3D information of an object using a rotating line laser, we must be aware of the plane of the line laser with respect to the camera coordinates at every rotating angle. This is done by estimating the rotation axis during calibration and then by rotating the laser at a predefined angle. Therefore, accurate calibration is crucial for 3D reconstruction. In this study, we propose a calibration method to estimate the geometrical relationship between the rotation axis of the line laser and the camera. Using the proposed method, we could accurately estimate the center of a cone or cylinder shape generated while the line laser was rotating. A simulation study was conducted to evaluate the accuracy of the calibration. In the experiment, we compared the results of the 3D reconstruction using our system and a commercial depth camera. The results show that the precision of our system is approximately 65% higher for plane reconstruction, and the scanning quality is also much better than that of the depth camera.

show abstract

On-Line Laser Triangulation Scanner for Wood Logs Surface Geometry Measurement

Cited by 23 publications

References 37 publications

Smart Harvest Operations and Timber Processing for Improved Forest Management

Smart Harvest Operations and Timber Processing for Improved Forest Management

A 3D Scanning System for Inverse Analysis of Moist Biological Samples: Design and Validation Using Tendon Fascicle Bundles

Development of a Wide Area 3D Scanning System with a Rotating Line Laser

Contact Info

Product

Resources

About