CMRT09: Object Extraction for 3D City Models, Road Databases and Traffic Monitoring - Concepts, Algorithms, and Evaluation
Beucher, S., 2007. Numerical residues. Image Vision Comput.
25(4), pp. 405-415.
Chen, X. and Yuille, A. L., 2004. Detecting and reading text in
natural scenes. Computer Vision and Pattern Recognition, IEEE
Computer Society Conference on 2, pp. 366-373.
Cortes, C. and Vapnik, V, 1995. Support-vector networks. Ma
chine Learning 20(3), pp. 273-297.
ImagEval, 2006. www.imageval.org.
Institut Géographique National, n.d. www.ign.fr.
¡Towns ANR project, 2008. www.itowns.fr.
Jian Liang, David Doermann and Huiping Li, 2005. Camera-
Based Analysis of Text and Documents: A Survey. International
Journal on Document Analysis and Recognition 7(2+3), pp. 83 -
104.
Joachims, T., n.d. svm. http://svmlight.joachims.org/.
Jung, K., Kim, K. and Jain, A., 2004. Text information extrac
tion in images and video: a survey. Pattern Recognition 37(5),
pp. 977-997.
Kavallieratou, E., Balcan, D., Popa, M. and Fakotakis, N., 2001.
Handwritten text localization in skewed documents. In: Interna
tional Conference on Image Processing, pp. I: 1102-1105.
Mancas-Thillou, C., 2006. Natural Scene Text Understanding.
PhD thesis, TCTS Lab of the Facult Polytechnique de Mons, Bel
gium.
Niblack, W., 1986. An Introduction to Image Processing.
Prentice-Hall, Englewood Cliffs, NJ.
Palumbo, P. W., Srihari, S. N., Soh, J., Sridhar, R. and Dem-
janenko, V, 1992. Postal address block location in real time.
Computer 25(7), pp. 34-42.
Retomaz, T. and Marcotegui, B., 2007. Scene text localiza
tion based on the ultimate opening. International Symposium on
Mathematical Morphology 1, pp. 177-188.
Sauvola, J. J., Seppànen, T., Haapakoski, S. and Pietikàinen, M.,
1997. Adaptive document binarization. In: ICDAR '91: Pro
ceedings of the 4th International Conference on Document Anal
ysis and Recognition, IEEE Computer Society, Washington, DC,
USA, pp. 147-152.
Serra, J., 1989. Toggle mappings. From pixels to features pp. 61-
72. J.C. Simon (ed.), North-Holland, Elsevier.
Shafait, F., Keysers, D. and Breuel, T. M., 2008. Efficient im
plementation of local adaptive thresholding techniques using in
tegral images. Document Recognition and Retrieval XV.
Szumilas, L., 2008. Scale and Rotation Invariant Shape Match
ing. PhD thesis, Technische universitt wien fakultt fr informatik.
Wahl, F., Wong, K. and Casey, R., 1982. Block segmentation
and text extraction in mixed text/image documents. Computer
Graphics and Image Processing 20(4), pp. 375-390.
Wolf, C., michel Jolion, J. and Chassaing, F., 2002. Text localiza
tion, enhancement and binarization in multimedia documents. In:
In Proceedings of the International Conference on Pattern Recog
nition (ICPR) 2002, pp. 1037-1040.
Figure 12: The initial image used for the test. This im
age is provided by the french ign (Institut Géographique
National, n.d.).
Figure 13: The image segmented by our algorithm TMMS.
Figure 14: All big regions are removed. Only the regions
of reasonable size are kept.
Figure 15: Remaining regions are classified by our system.
Text region (in green) are kept, non text region (in red) are
removed.
Figure 16: Isolated text regions are removed and remaining
regions are grouped.
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