Experimentation of structured light and stereo vision for underwater 3D reconstruction

Bruno, Fabio; Bianco, Gianfranco; Muzzupappa, Maurizio; Barone, Sandro; Razionale, Armando Viviano

doi:10.1016/j.isprsjprs.2011.02.009

Cited by 210 publications

(126 citation statements)

References 36 publications

(33 reference statements)

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“…by Korduan (Korduan et al 2003). However as reported by Bruno (Bruno et al 2011), there occurred differences in the parameters of air and water calibration, probably due to deviations of the exact camera placement. Hence, additional correction parameters describing the distortion are necessary, probably depending on the object distance.…”

Section: Modelmentioning

confidence: 71%

“…This could be obtained either by performing a calibration using underwater image recordings (as proposed e.g. by Bryant (Bryant et al 2000) or Bruno (Bruno et al 2011) ) or performing an air calibration and transforming the intrinsic parameters and the distortion as proposed by Lavest (Lavest et al 2003). Additionally, a translation of the projection centre can be estimated (see next section).…”

Section: Approaches For Underwater Calibrationmentioning

confidence: 99%

“…First experimentation using a stereo camera setup and fringe projection technique for structured illumination was performed by Bruno (Bruno et al 2011). There the suitability of the measurement principle for underwater 3D application is shown, and potential applications are discussed.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Compact Handheld Fringe Projection Based Underwater 3d-Scanner

Bräuer-Burchardt

Heinze²,

Schmidt³

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:A new, fringe projection based compact handheld 3D scanner for the surface reconstruction of measurement objects under water is introduced. The weight of the scanner is about 10 kg and can be used in a water depth of maximal 40 metres. A measurement field of about 250 mm x 200 mm is covered under water, and the lateral resolution of the measured object points is about 150 µm. Larger measurement objects can be digitized in a unique geometric model by merging subsequently recorded datasets. The recording time for one 3D scan is a third of a second. The projection unit for the structured illumination of the scene as well as the computer for device control and measurement data analysis are included into the scanners housing. A display on the backside of the device realizes the graphical presentation of the current measurement data. It allows the user to evaluate the quality of the measurement result in real-time already during the recording of the measurement under water. For the calibration of the underwater scanner a combined method of air-and water-calibration was developed which needs only a few recorded underwater images of a plane surface and an object with known lengths. First measurement results obtained with the new scanner are presented.

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Section: Modelmentioning

confidence: 71%

Section: Approaches For Underwater Calibrationmentioning

confidence: 99%

See 1 more Smart Citation

Compact Handheld Fringe Projection Based Underwater 3d-Scanner

Bräuer-Burchardt

Heinze²,

Schmidt³

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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show abstract

“…Traditional 2D vision is not applicable to inspect the object with free surface such as the turbine blade. 3D vision provides an alternative for these problems with more flexibility while little cost added, including various technologies [42], which is a powerful tool in industrial quality inspection [43], welding [44], lens quality inspection [45], thin-walled components inspection [46] and suitable for sorts of working conditions [47][48][49].…”

Section: Pilot Study: 3d Iqismentioning

confidence: 99%

Towards zero-defect manufacturing (ZDM)—a data mining approach

Wang

2013

Adv. Manuf.

114

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The quality of a product is dependent on both facilities/equipment and manufacturing processes. Any error or disorder in facilities and processes can cause a catastrophic failure. To avoid such failures, a zero-defect manufacturing (ZDM) system is necessary in order to increase the reliability and safety of manufacturing systems and reach zero-defect quality of products. One of the major challenges for ZDM is the analysis of massive raw datasets. This type of analysis needs an automated and self-organized decision making system. Data mining (DM) is an effective methodology for discovering interesting knowledge within a huge datasets. It plays an important role in developing a ZDM system. The paper presents a general framework of ZDM and explains how to apply DM approaches to manufacture the products with zero-defect. This paper also discusses 3 ongoing projects demonstrating the practice of using DM approaches for reaching the goal of ZDM.

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“…This included (Bruno et al, 2011) who demonstrated a successful method for 3-dimensional close range reconstruction of objects using stereo vision and structured light while (Carreras et al, 2003) and showed navigation and localization using data extracted from a camera image of a known mosaic pattern located on the floor of a pool. Work describing the use of lasers for underwater range estimation have been described in several papers.…”

Section: Introductionmentioning

confidence: 99%

Short-Range Sensor for Underwater Robot Navigation using Line-lasers and Vision

et al. 2015

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This paper investigates a minimalistic laser-based range sensor, used for underwater inspection by Autonomous Underwater Vehicles (AUV). This range detection system system comprise two lasers projecting vertical lines, parallel to a camera's viewing axis, into the environment. Using both lasers for distance estimation, the sensor offers three dimensional interpretation of the environment. This is obtained by triangulation of points extracted from the image using the Hough Transform. We evaluate the system in simulation and by physical proof-of-concept experiments on an OpenROV platform.

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Experimentation of structured light and stereo vision for underwater 3D reconstruction

Cited by 210 publications

References 36 publications

Compact Handheld Fringe Projection Based Underwater 3d-Scanner

Compact Handheld Fringe Projection Based Underwater 3d-Scanner

Towards zero-defect manufacturing (ZDM)—a data mining approach

Short-Range Sensor for Underwater Robot Navigation using Line-lasers and Vision

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