članak: 1 od 1  
Journal of Automatic Control
2006, vol. 16, br. 1, str. 51-56
jezik rada: engleski
neklasifikovan
doi:10.2298/JAC0601051B

Cursive word raw segmentation based on scanning Skew slots
(naslov ne postoji na srpskom)
Univerzitet u Prištini (Kosovska Mitrovica), Fakultet tehničkih nauka

e-adresa: babic57@eunet.yu

Sažetak

(ne postoji na srpskom)
In this paper we present an outline of a method for low-level structural analysis of cursive words by scanning skew slots which produce histograms or word profiles. Having different angles slots can detect corresponding structural details - writing strokes and their directions. The word baseline which serves as a reference for slot angles, can be easily revealed Also from word profiles taken by different slots we can get candidate spots for preliminary word segmentation. Although very simple this segmentation approach does not request any preprocessing of input bitmap image, including deskew, deslant or smoothing, but it is not resistant on patch noise. In the same manner it is possible to structurally examine isolated word segments without interference with neighboring ones, in order to combine prominent details from various histograms and get lexicon-like segment description. Finally, we announce further improvement of analytic abilities of this method through partial histograms which more successfully cope with specific structural cases.

Ključne reči

skew correction; slant correction; base line detection; segmentation

Reference

Babić, R.V. (1993) An approach to recognition of handwriting elements. Pristina: Faculty of Electrical Engineering, PhD dissertation
Babić, R.V. (2001) A method of adaptive rotation-free structural coding of handwritten characters. Journal of Automatic Control, vol. XI (1), str. 49-59
Božinović, R.M., Shrihari, S.N. (1989) Off-line cursive script recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, br. 1, str. 68-83
Casey, R.G., Lecolinet, E. (1996) A survey of methods and strategies in character segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, br. 7, str. 690-706
Glauberman, M.H. (1956) Character recognition for business machines. Electronics, str. 132-136, Feb
Kuan, C.L., Srihari, S.N. (1988) A stroke-based approach to handwritten numeral recognition. u: USPS Advanced Technology Conference, Washington DC: US Postal Service, str. 1033-1041
Larson, K. (2004) The science of word recognition advanced reading technology. Microsoft Corporation, July
Liang, J., i dr. (2001) An optimization methodology for document structure extraction on Latin character documents. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, br. 7, July str. 719-735
Liu, Y., Srihari, S. (1997) Document image binarization based on texture features. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, br. 5, str. 540-544, May
Madhvanath, S., Kleinberg, E., Govindaraju, V. (1999) Holistic verification of handwritten phrases. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, br. 12, str. 1344-1357, Dec
Madhvanath, S., Govindaraju, V. (2001) The role of holistic paradigms in handwritten word recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, br. 2, str. 149-164, Feb
Mori, S., i dr. (1992) Historical review of OCR research and development. Proc. IEEE, vol. 80, br. 7, str. 1029-1058, July, Special Issue on OCR
Nicchiotti, G., i dr. (2000) A simple and effective cursive word segmentation method. u: Proceedings of the Seventh International Workshop on Frontiers in Handwriting Recognition, Amsterdam, Sept. 11-13, pp 499-504
Perotto, P.G. (1963) A new method for automatic character recognition. IEEE Transactions on Electron. Comput, vol.EC-12, str. 521-526, Oct
Schurmann, J., i dr. (1992) Document analysis: From pixels to content. Proc. IEEE, vol. 80, br. 7, str. 1101-1119, July, Special Issue on OCR
Steinherz, T., Rivlin, E., Intrator, N. (1999) Offline cursive script word recognition: A survey. International Journal on Document Analysis and Recognition, 2: str. 90-110
Stringa, L. (1992) Automatic book recognition. u: Symposium on Document Analysis and Information Retrieval, Las Vegas, str. 119-207
Zhu, Y., i dr. (2001) Font recognition based on global texture analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, br. 10, str. 1192-1206, Oct