A Stereo Vision System for Top View Book Scanners

This paper proposes a novel stereo vision technique for top view book scanners which provide us with dense 3d point clouds of page surfaces. This is a precondition to dewarp bound volumes independent of 2d information on the page. Our method is based on algorithms, which normally require the projection of pattern sequences with structured light. We use image sequences of the moving stripe lighting of the top view scanner instead of an additional light projection. Thus the stereo vision setup is simplified without losing measurement accuracy. Furthermore we improve a surface model dewarping method through introducing a difference vector based on real measurements. Although our proposed method is hardly expensive neither in calculation time nor in hardware requirements we present good dewarping results even for difficult examples.




References:
[1] Donescu, A., Bouju, A., Quillet, V.: Former books digital processing:
image warping. In: Proc. Workshop on Document Image Analysis.
(1997) 5-9
[2] Yamashita, A., A.Kawarago, Kaneko, T., Miura, K.: Shape reconstruction
and image restoration for non-flat surfaces of documents with a
stereo vision system. In: Proc. of 17th International Conference on
Pattern Recognition. Volume 1. (2004) 486-489
[3] Chu, K.B., Zhang, L., Zhang, Y., Tan, C.L.: A fast and stable approach
for restoration of warped document images. In: Proceedings of the
Eighth International Conference on Document Analysis and Recognition.
(2005) 384-388
[4] Brown, M., Seales, W.: Image restoration of arbitrarily warped documents.
IEEE Transactions on Pattern Analysis and Machine Intelligence
26 (2004) 1295-1306
[5] Tan, C.L., Zhang, L., Zhang, Z., Xia, T.: Restoring warped document
images through 3d shape modeling. IEEE Transactions on Pattern
Analysis and Machine Intelligence 28 (2006) 195-208
[6] Ulges, A., Lampert, C.H., Breuel, T.M.: Document image dewarping
using robust estimation of curled text lines. Proc. of 8th International
Conference on Document Analysis and Recognition 0 (2005) 1001-1005
[7] Liang, J., Doermann, D., Li, H.: Camera-based analysis of text and
documents: a survey. International Journal on Document Analysis and
Recognition 7 (2005) 84-104
[8] Lilienblum, E., Michaelis, B.: Digitalisation of warped documents
supported by 3d-surface reconstruction. In: The 5th International
Conference on Computer Vision Systems Conference Paper. (2007) DOI:
10.2390/biecoll-icvs2007-69.
[9] Blais, F.: A review of 20 years of range sensor development. Journal
of Electronic Imaging 13 (2004) 231-243
[10] Valkenburg, R.J., McIvor, A.M.: Accurate 3d measurement using a
structured light system. Image and Vision Computing 16 (1998) 99-
110
[11] Albrecht, P., Michaelis, B.: Improvement of the spatial resolution
of an optical 3-d measurement procedure. In: IEEE Transactions on
Instrumentation and Measurement. Volume 47., Brisbane (1998) 158-
162
[12] Luhmann, T., Robson, S., Kyle, S., Harley, I.: Close Range Photogrammetry.
Whittles Publishing (2006)
[13] Lilienblum, E., Michaelis, B.: Optical 3d surface reconstruction by a
multi-period phase shift method. Journal of Computers (JCP) 2 (2007)
73-83
[14] Liang, J., DeMenthon, D., Doermann, D.: Geometric rectification
of camera-captured document images. IEEE Transactions on Pattern
Analysis and Machine Intelligence (2007) (PrePrint).
[15] Lilienblum, E., Michaelis, B.: Book scanner dewarping with weak 3d
measurements and a simplified surface model. In: Discrete Geometry
for Computer Imagery - DGCI 2008. Volume 4992 of LNCS. (2008)
529-540