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 photogram-metric 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.
Al-Ruzouq, R. (2012) Photogrammetry for Archaeological Documentation and Cultural Heritage Conservation. Special Applications of Photogrammetry, InTech. https://doi.org/10.5772/35314
Elaksher, A.F. (2012) Potential of Using Automatically Extracted Straight Lines in Rectifying High-Resolution Satellite Images. International Journal of Remote Sensing, 33, 1-12. https://doi.org/10.1080/01431161.2010.489058
Ahmad, A. (2011) Digital Mapping Using Low Altitude UAV. Pertanika Journal of Science and Technology, 19, 51-58.
Mitishita, E., Habib, A., Centeno, J., Machado, A., Lay, J. and Wong, C. (2008) Photogrammetric and Lidar Data Integration Using the Centroid of a Rectangular Roof as a Control Point. The Photogrammetric Record, 23, 19-35. https://doi.org/10.1111/j.1477-9730.2008.00464.x
Falkingham, P.L., Bates, K.T. and Farlow, J.O. (2014) Historical Photogrammetry: Bird’s Paluxy River Dinosaur Chase Sequence Digitally Reconstructed as It Was Prior to Excavation 70 Years Ago. PloS ONE, 9, e93247. https://doi.org/10.1371/journal.pone.0093247
Nebiker, S., Lack, N. and Deuber, M. (2014) Building Change Detection from Historical Aerial Photographs Using Dense Image Matching and Object-Based Image Analysis. Remote Sensing, 6, 8310-8336. https://doi.org/10.3390/rs6098310
Albuquerque, M.T.D., Sanz, G., Oliveira, S.F., Martínez-Alegría, R. and Antunes, I.M.H.R. (2013) Spatio-Temporal Groundwater Vulnerability Assessment—A Coupled Remote Sensing and GIS Approach for Historical Land Cover Reconstruction. Water Resources Management, 27, 4509-4526. https://doi.org/10.1007/s11269-013-0422-0
Nocerino, E., Menna, F. and Remondino, F. (2012) Multi-Temporal Analysis of Landscapes and Urban Areas. International Archives of Photogrammetry, Remote Sensing & GIS, 85-90.
De Rose, R.C. and Basher, L.R. (2011) Measurement of River Bank and Cliff Erosion from Sequential LIDAR and Historical Aerial Photography. Geomorphology, 126, 132-147. https://doi.org/10.1016/j.geomorph.2010.10.037
Mackey, B.H. and Roering, J.J. (2011) Sediment Yield, Spatial Characteristics, and the Long-Term Evolution of Active Earthflows Determined from Airborne LiDAR and Historical Aerial Photographs, Eel River, California. Geological Society of America Bulletin, 123, 1560-1576. https://doi.org/10.1130/B30306.1
Sevara, C. (2016) Capturing the Past for the Future: An Evaluation of the Effect of Geometric Scan Deformities on the Performance of Aerial Archival Media in Image-Based Modelling Environments. Archaeological Prospection, 23, 325-334. https://doi.org/10.1002/arp.1539
Gruber, M. and Leberl, F. (2001) Description and Evaluation of the High Quality Photogrammetric Scanner UltraScan 5000. ISPRS Journal of Photogrammetry and Remote Sensing, 55, 313-329. https://doi.org/10.1016/S0924-2716(01)00024-7
Mitrovic, M., Cvijetinovic, Z. and Mihajlovic, D. (2004) Procedures and Experiences on Using Desktop Scanner for Orthophoto Production. 20th ISPRS Congress, Istanbul, 12-23 July 2004, 53-58.
Göröcs, Z. and Ozcan, A. (2014) Biomedical Imaging and Sensing using Flatbed Scanners. Lab on a Chip, 14, 3248-3257. https://doi.org/10.1039/C4LC00530A
Gergel, S.E., Coops, N.C. and Morgan, J.L. (2010) Aerial Photography: A Rapidly Evolving Tool for Ecological Management. Bioscience, 60, 47-59.
Yousefhussien, M., Easton Jr., R.L., Ptucha, R.W., Shaw, M.Q., Bradburn, B.M., Wagner, J., Saber, E., et al. (2015) Flatbed Scanner Simulation to Analyze the Effect of Detector’s Size on Color Artifacts. Proceedings of the SPIE, 9401, 94010H.
Zheleznyak, A.G. and Sidorov, V.G. (2015) Flatbed Scanner as an Instrument for Physical Studies. St. Petersburg Polytechnical University Journal: Physics and Mathematics, 1, 134-141. https://doi.org/10.1016/j.spjpm.2015.04.001
Williams, G.J., Maddox, B.R., Chen, H., Kojima, S. and Millecchia, M. (2014) Calibration and Equivalency Analysis of Image Plate Scanners A. Review of Scientific Instruments, 85, 11E604. https://doi.org/10.1063/1.4886390
Baltsavias, E.P., Haering, S. and Kersten, T.P. (1997) Geometric and Radiometric Performance Evaluation of the Leica/Helava DSW200 Photogrammetric Film Scanner. Proceedings of the SPIE, 3174, 157-173.
Bethel, J. (1994) Calibration of a Photogrammetric Image Scanner. Technical Papers, ASPRS/ACSM Annual Convention, Reno, 25-28 April 1994, Vol. 1, 81-88.
Ruzgienè, B., Bagdžiūnaitè, R. and Ruginytè, V. (2012) Scanning Aerial Photos using a Non-Professional Scanner. Geodesy and Cartography, 38, 118-121. https://doi.org/10.3846/20296991.2012.728901
El-Ashmawy, K.L. (2014) Using Low Cost DeskTop Publishing (DTP) Scanners for Aerial Photogrammetry. Journal of Geosciences and Geomatics, 2, 107-113.
De Vicente, J., Sánchez-Pérez, A.M., Maresca, P., Caja, J. and Gómez, E. (2015) A Model to Transform a Commercial Flatbed Scanner into a Two-Coordinates Measuring Machine. Measurement, 73, 304-312. https://doi.org/10.1016/j.measurement.2015.05.029
Jones, M.P., Callahan, R.N. and Bruce, R.D. (2012) Dimensional Measurement Variation of Scanned Objects using Flatbed Scanners. Journal of Technology, Management & Applied Engineering, 28, 1-12.
Wyatt, M. and Nave, G. (2017) Evaluation of Resolution and Periodic Errors of a Flatbed Scanner Used for Digitizing Spectroscopic Photographic Plates. Applied Optics, 56, 3744-3749. https://doi.org/10.1364/AO.56.003744
De Vicente, J., Sánchez-Perez, A.M., Berzal, M., Maresca, P. and Gómez, E. (2013) Uncertainty in Ellipse Fitting using a Flatbed Scanner: Development and Experimental Verification. Measurement Science and Technology, 25, Article ID: 015005. https://doi.org/10.1088/0957-0233/25/1/015005
Kangasrääsiö, J. and Hemming, B. (2009) Calibration of a Flatbed Scanner for Traceable Paper Area Measurement. Measurement Science and Technology, 20, Article ID: 107003. https://doi.org/10.1088/0957-0233/20/10/107003
Poppinga, D., Schoenfeld, A.A., Doerner, K.J., Blanck, O., Harder, D. and Poppe, B. (2014) A New Correction Method Serving to Eliminate the Parabola Effect of Flatbed Scanners Used in Radiochromic Film Dosimetry. Medical Physics, 41, Article ID: 021707. https://doi.org/10.1118/1.4861098
Meng, G., Wang, Y., Qu, S., Xiang, S. and Pan, C. (2014) Active Flattening of Curved Document Images via Two Structured Beams. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, 23-28 June 2014, 3890-3897. https://doi.org/10.1109/CVPR.2014.497
Suzuki, Y., Yamashita, A. and Kaneko, T. (2007) Correction of Geometric and Photometric Distortion of Document Images using a Stereo Camera System. Proceedings of the IAPR Conference on Machine Vision Applications, Tokyo, 16-18 May 2007, 215-218.
Zhang, L., Zhang, Z., Tan, C.L. and Xia, T. (2005) 3D Geometric and Optical Modeling of Warped Document Images from Scanners. Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, 20-25 June 2005, Vol. 1, 337-342.
He, Y., Pan, P., Xie, S., Sun, J. and Naoi, S. (2013) A Book Dewarping System by Boundary-Based 3D Surface Reconstruction. 12th International Conference on Document Analysis and Recognition, Washington DC, 25-28 August 2013, 403-407.