Abstract
The multi-orientation occurs frequently in ancient handwritten documents, where the writers try to update a document by adding some annotations in the margins. Due to the margin narrowness, this gives rise to lines in different directions and orientations. Document recognition needs to find the lines everywhere they are written whatever their orientation. This is why we propose in this paper a new approach allowing us to extract the multi-oriented lines in scanned documents. Because of the multi-orientation of lines and their dispersion in the page, we use an image meshing allowing us to progressively and locally determine the lines. Once the meshing is established, the orientation is determined using the Wigner–Ville distribution on the projection histogram profile. This local orientation is then enlarged to limit the orientation in the neighborhood. Afterward, the text lines are extracted locally in each zone basing on the follow-up of the orientation lines and the proximity of connected components. Finally, the connected components that overlap and touch in adjacent lines are separated. The morphology analysis of the terminal letters of Arabic words is here considered. The proposed approach has been experimented on 100 documents reaching an accuracy of about 98.6%.
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References
Akiyama T., Hagita N.: Automatic entry system for printed documents. Pattern Recognit. 23, 1141–1154 (1990)
Antonacopoulos A., Karatzas D.: Document image analysis for world war ii personal records. Int. Workshop Document Image Anal. Libr. 0, 336–343 (2004)
Auger F., Doncarli C.: Quelques commentaires sur des représentations temps-fréquence proposées récemment”. Traitement du Signal 9(1), 3–25 (1992)
Bennasri A., Zahour A., Taconet B.: Extraction des lignes d’un texte manuscrit arabe. Vis. Interface’ 99(13), 42–48 (1999)
Boussellaa, W., Zahour, A., Elabed, H., Benabdelhafid, A., Alimi, A.M.: Unsupervised block covering analysis for text-line segmentation of Arabic ancient handwritten document images. International Conference on Pattern Recognition, pp. 1929–1932 (2010)
Bukhari, S.S., Shafait, F., Breuel, T.M.: Segmentation of curled textlines using active contours. The Eighth IAPR Workshop on Document Analysis Systems, (DAS 2008), pp. 270–277 (2008)
Bukhari, S.S., Shafait, F., Breuel, T.M.: Performance evaluation of curled textlines segmentation algorithms. ninth IAPR Workshop on Document Analysis Systems, DAS’10, Boston, MA, USA (2010)
Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. International Conference on Computer Vision, pp. 694–699 (1995)
Classen, T.A.C.M., Mecklenbrauker, W.F.G.: The Wigner distribution—a tool for time frequency analysis, Parts I–III, Philips J. Res., vol. 35, Part I: n3, p. 217-250; Part II n4/5, pp. 372–389; Part III: n6, pp. 372–389 (1980)
Cohen L.: Generalized phase-space distribution functions. J. Math. Phys. 7(5), 781–786 (1966)
Coüasnon, B., Camillerapp, J.: Dmos, une méthode générique de reconnaissance de documents : évaluation sur 60,000 formulaires du xixe siécle. In: Colloque International Francophone sur l’crit et le Document (CIFED’02), pp. 225–234 (2002)
Du X., Pan W., Bui T.D.: Text line segmentation in handwritten documents using Mumford-Shah model. Pattern Recogn. 42(12), 3136–3145 (2009)
Escudié B., Gréa J.: Sur une formulation générale de la représentation en temps et en fréquence dans l’analyse des signaux d’énergie finie. CR. Acad. Sci. Paris 283, 1049–1051 (1976)
Feldbach, M., Tönnies, K.D.: Line detection and segmentation in historical church registers. In: ICDAR’01: Proceedings of the Sixth International Conference on Document Analysis and Recognition, Washington, DC, USA, IEEE Computer Society, pp. 743–748 (2001)
Flandrin P.: Time-frequency/time-scale analysis. Academic Press, San Diego CA (1999)
Hlawatsch F., Boudreaux-Bartels G.F.: Linear and quadratic time-frequency signal representation. IEEE Signal Process. Mag. 9(2), 21–67 (1992)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. In: Proceedings of the 1st ICCV, pp. 259–268 (1987)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. In: Proceedings of the 1st ICCV, 987, pp. 259–268 (1988)
Kavallieratou E., Fakotakis N., Kokkinakis G.: Skew angle estimation in document processing using cohen’s class distributions. Pattern Recogn. Lett. 20, 11–13 (1999)
Kavallieratou E., Fakotakis N., Kokkinakis G.: Skew angle estimation for printed and handwritten documents using the wigner-ville distribution. Image Vis. Comput. 20, 813–824 (2002)
Kumar, J., Abd-Almageed, W., Kang, L., Doermann, D.: Handwritten Arabic text line segmentation using affinity propagation. In: Document Analysis Systems, pp. 135–142 (2010)
Le Bourgeois F., Emptoz H., Trinh E., Duong J.: Networking digital document images. Int. Conf. Document Anal. Recognit. 0, 0379 (2001)
Leitner, F., Cinquin, P.: From splines and snakes to snake splines. In: Selected Papers from the Workshop on Geometric Reasoning for Perception and Action, pp. 264–281. Springer, London, UK (1993)
Li Y., Zheng Y., Doermann D., Jaeger S.: Script-independent text line segmentation in freestyle handwritten documents. IEEE Trans. Pattern Anal. Mach. Intell. 30(8), 1313–1329 (2008)
Likforman-Sulem, L., Faure, C.: Extracting lines on handwritten documents by perceptual grouping. In: Faure, C., Keuss, P., Lorette, G., Winter, A. (eds.) Advances in handwiting and drawing: multidisciplinary approach, pp. 21–38 (1994)
Likforman-Sulem L., Hanimyan A., Faure C.: A hough based algorithm for extracting text lines in handwritten documents. Int. Conf. Document Anal. Recognit. 2, 774–777 (1995)
Louloudis G., Gatos B., Pratikakis I., Halatsis C.: Text line and word segmentation of handwritten documents. Pattern Recognit. 42(12), 3169–3183 (2009)
Mahadevan, U., Nagabushnam, R.C.: Gap metrics for word separation in handwritten lines. In: ICDAR ’95: Proceedings of the Third International Conference on Document Analysis and Recognition, vol. 1, pp. 124–127 (1995)
Montagnat J., Delingette H., Ayache N.: A review of deformable surfaces: topology, geometry and deformation. J. Image Vis. Comput. 19(14), 1023–1040 (2001)
Mumford D., Shah J.: Optimal approximation by piecewise smooth functional and associated variational problems. Commun. Pure Appl. Math. 42, 577–685 (1989)
Nicolaou A., Gatos B.: Handwritten text line segmentation by shredding text into its lines. Int. Conf. Document Anal. Recognit. 0, 626–630 (2009)
Nicolas, S., Paquet, T., Heutte, L.: Text line segmentation in handwritten document using a production system. In: Ninth International Workshop on Frontiers in Handwriting Recognition, pp. 245–250 (2004)
Osher S., Paragios N.: Geometric level set methods in imaging, vision, and graphics. Springer, New York (2003)
Oztop E., Mulayim A.Y., Atalay V., Yarman Vural F.: Repulsive–attractive network for baseline extraction on document images. Signal Process. 75, 1–10 (1999)
Pavlidis T., Zhou J.: Page segmentation and classification. Comput. Vis. Graph. Image Process. 54(2), 484–496 (1992)
Peake G.S., Tan T.N.: A general algorithm for document skew angle estimation. IEEE Int. Conf. Image Process 2, 230–233 (1997)
Pluempitiwiriyawej C., Moura J.M.F., Wu Y.J.L., Ho C.: stacs: new active contour scheme for cardiac MR image segmentation. IEEE Trans. Med. Imaging 24(5), 593–603 (2005)
Postl, W.: Detection of linear oblique structures and skew scan in digitized documents. In: Proceedings of the Eighth International Conference on Pattern Recognition, IEEE CS Press, Los Alamitos, CA, pp. 687–689 (1986)
Pu, Y., Shi, Z.: A natural learning algorithm based on hough transform for text lines extraction in handwritten document. In: Proceedings of the 6th International Workshop on Frontiers in Handwriting Recognition, pp. 637–646 (1998)
Ramlau R., Ring W.: A Mumford-Shah level-set approach for the inversion and segmentation of X-ray tomography data. J. Comput. Phys. 221(2), 539–557 (2007)
Saha, S., Basu, S., Nasipuri, M., Basu, D.Kr.: A Hough transform based technique for text segmentation. In: Computing Research Repository (2010)
Sethian J.A.: Curvature and the evolution of fronts. Commun. Math. Phys. 101(4), 487–499 (1985)
Shapiro V., Gluchev G., Sgurev V.: Handwritten document image segmentation and analysis. Pattern Recogn. Lett. 14(1), 71–78 (1993)
Shi, Z., Govindaraju, V.: Line separation for complex document images using fuzzy run length. In: International Workshop on Document Image Analysis for Libraries (2004)
Xu, C., Prince, J.L.: Gradient vector flow: a new external force for snakes. In: Proceedings of the IEEE Conference on Comp. Vis. Patt. Recog. (CVPR), pp. 66–71 June (1997)
Yin, F., Liu, C.-L.: Handwritten text line segmentation by clustering with distance metric learning. In: Proceedings of 11th ICFHR, pp. 229–234 (2008)
Zahour, A., Taconet, B., Ramdane, S.: Contribution à la segmentation de textes manuscrits anciens. In: Conférence Internationale Francophone sur l’Ecrit et le Document (CIFED’04), 06 (2004)
Zheng, Y., Li, H., Doermann, D.: A model-based line detection algorithm in documents. International Conference on Document Analysis and Recognition, vol. 1, p. 44 (2003)
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Ouwayed, N., Belaïd, A. A general approach for multi-oriented text line extraction of handwritten documents. IJDAR 15, 297–314 (2012). https://doi.org/10.1007/s10032-011-0172-6
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DOI: https://doi.org/10.1007/s10032-011-0172-6