A model to transform a commercial flatbed scanner into a two-coordinates measuring machine

Vicente, José Miguel Gómez de; Sánchez-Pérez, Ana; Maresca, P.; Caja, J.; Gómez, E.

doi:10.1016/j.measurement.2015.05.029

Cited by 10 publications

(13 citation statements)

References 17 publications

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“…Nevertheless, whereas high scanning time could be assumed within the scope of this research, files size of several hundred MB turned out to be a major problem for subsequent image processing. Some researchers avoid this problem by reducing image resolution and/or narrowing scanning area [27,31]. In the present work, since considering the whole range of available resolutions was among the initial research purposes, a restriction of maximum allowable scanning area was imposed.…”

Section: Materials and Equipmentmentioning

confidence: 99%

“…The first method is based on the one proposed by De Vicente [27], as it was thereafter implemented by Majarena [29]. This method assumes that the coordinate system of the flatbed scanner (PQ, see Figure 9) is not a Cartesian one (XY), but in fact formed by a tilted, non-orthogonal axis with dissimilar scales (due to slight differences in pixels size).…”

Section: Sensor Adjustmentmentioning

confidence: 99%

“…The consequences of image deformation cannot be considered negligible for verification purposes, since other works also reported the existence of periodic errors that could reach 50 µm along the scanning movement direction [26], whereas less relevant errors showing no periodic behavior would be found in the direction parallel to the scan head.Since image deformation issues had been proved to be inherent to flatbed scanning, a research effort has been paid to deformation modelling and sensor adjustment. De Vicente [27] proposed a model that allows a flatbed scanner to be used as a bi-dimensional coordinate measurement machine. They divided their procedure in two stages: in the initial one they performed an adjustment based on self-calibration [28] of the measuring system where the geometrical errors of the equipment are eliminated; in the final stage a calibration procedure is performed, so that a calibration parameter C k is calculated.…”

mentioning

confidence: 99%

“…Since image deformation issues had been proved to be inherent to flatbed scanning, a research effort has been paid to deformation modelling and sensor adjustment. De Vicente [27] proposed a model that allows a flatbed scanner to be used as a bi-dimensional coordinate measurement machine. They divided their procedure in two stages: in the initial one they performed an adjustment based on self-calibration [28] of the measuring system where the geometrical errors of the equipment are eliminated; in the final stage a calibration procedure is performed, so that a calibration parameter C k is calculated.…”

mentioning

confidence: 99%

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Layer Contour Verification in Additive Manufacturing by Means of Commercial Flatbed Scanners

Blanco

Fernández

Noriega

et al. 2019

Sensors

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Industrial adoption of additive manufacturing (AM) processes demands improvement in the geometrical accuracy of manufactured parts. One key achievement would be to ensure that manufactured layer contours match the correspondent theoretical profiles, which would require integration of on-machine measurement devices capable of digitizing individual layers. Flatbed scanners should be considered as serious candidates, since they can achieve high scanning speeds at low prices. Nevertheless, image deformation phenomena reduce their suitability as two-dimensional verification devices. In this work, the possibilities of using flatbed scanners for AM contour verification are investigated. Image distortion errors are characterized and discussed and special attention is paid to the plication effect caused by contact imaging sensor (CIS) scanners. To compensate this phenomena, a new local distortion adjustment (LDA) method is proposed and its distortion correction capabilities are evaluated upon actual layer contours manufactured on a fused filament fabrication (FFF) machine. This proposed method is also compared to conventional global distortion adjustment (GDA). Results reveal quasi-systematic deformations of the images which could be minimized by means of distortion correction. Nevertheless, the irregular nature of such a distortion and the superposition of different errors penalize the use of GDA, to the point that it should not be used with CIS scanners. Conclusions indicate that LDA-based correction would enable the use of flatbed scanners in AM for on-machine verification tasks.Sensors 2020, 20, 1 2 of 24 following parts. Although this is the usual approach for quality assurance in AM it does not permit adoption of close-loop in-process improvements, and implies that optimization could not be done without previously manufacturing test specimens.Nevertheless, regarding the dimensional quality of manufactured parts, one key achievement would be to build layer contours that accurately follow theoretical profiles. This possibility would require on-machine integration of measurement devices to evaluate in-layer quality. The use of sensors capable of verifying each individual layer and checking the accuracy in contour tracing would allow for correction of the next layers. They would also make unnecessary previous testing of each particular geometry. Therefore, real-time, in-line metrology is commonly reported to be among the main challenges for AM development [9]. Contour verification could be carried out by means of different technologies, like structured light [7], conoscopic holography [10], coordinate measuring machine (CMM) optical probes [11] or ad hoc Charge-Couple Device (CCD) based instrumentation [12,13]. Nevertheless, computer vision based on flatbed scanner images should be considered as a serious candidate, since it can meet high scanning speeds at low prices.Flatbed scanners are optical devices commonly used to capture digital images of flat elements, such as sheets of paper or photographs. Nevertheless, image...

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Section: Materials and Equipmentmentioning

confidence: 99%

Section: Sensor Adjustmentmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Layer Contour Verification in Additive Manufacturing by Means of Commercial Flatbed Scanners

Blanco

Fernández

Noriega

et al. 2019

Sensors

View full text Add to dashboard Cite

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“…Yet, he concluded that the achieved precision is suitable for planimetric maps of 1:5000 scale and to produce contours of one-meter interval. A procedure was outlined in [23] to convert flatbed scanners to traceable table to measure 2D coordinates. For calibrating the scanner, a calibration parameter was added to the transformation model and estimated through the measure of a line scale.…”

Section: Introductionmentioning

confidence: 99%

Geometric Calibration of Low-Cost Flatbed Scanners for Large Scale Mapping Applications

Elaksher¹,

Ali²

2018

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Scanning hardcopy non-metric images is one of the most important sources in digital mapping. Low-cost scanners are still widely used in many applications as they can produce digital images of comparable precisions to those produced by expensive professional scanners. Yet, inexpensive scanners introduce geometrical distortions in the measured image coordinates that must be assessed and compensated before using their products for further analysis. In this article, several 2D-to-2D transformation models were investigated to calibrate flatbed scanners with different resolutions and sizes. We evaluated the potential of each model using two gridded-crosses plotted on high-quality transparent sheets. Control coordinates were provided through a photogrammetric analytical plotter. After scanning the sheets, least squares matching was applied to determine the precise locations of the crosses. By comparing the control coordinates and those estimated from digitized images, it was found that the mathematical model based on the projective transformation gives the best results for standardizing the geometric properties of flatbed scanners. The results show that scanning resolution of 2400 dpi achieves the requirements for large-scale mapping applications.

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Determining the optical properties of solar cells using low cost scanners

Juhl

Veettil

Scardera

et al. 2022

Sci Rep

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This paper investigates the use of consumer flatbed scanners for the use of monitoring solar cell precursors. Two types of scanners are investigated a contact image scanner and scanners with more conventional optical setups. The contact image sensor is found to be more suitable as it does not require additional flat field calibration. The scanners’ ability to monitor variation in sample texture was investigated by monitoring the reflection of multi-crystalline and mono-crystalline textured wafers. For a baseline, a comparison was made to a high-end tool used in industry. Both good qualitative agreement and statistical correlation were achieved between the scanner and industry tool for the isotropic multi-crystalline wafers.

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A model to transform a commercial flatbed scanner into a two-coordinates measuring machine

Cited by 10 publications

References 17 publications

Layer Contour Verification in Additive Manufacturing by Means of Commercial Flatbed Scanners

Layer Contour Verification in Additive Manufacturing by Means of Commercial Flatbed Scanners

Geometric Calibration of Low-Cost Flatbed Scanners for Large Scale Mapping Applications

Determining the optical properties of solar cells using low cost scanners

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