Kołodziej, Joanna - ed. ; Pllana, Sabri - ed. ; Vitabile , Salvatore - ed.
There are a large number of historical documents in libraries and other archives throughout the world. Most of them are written by hand. In many cases they exist in only one specimen and are hard to reach. Digitization of such artifacts can make them available to the community. But even digitized, they remain unsearchable, and an important task is to draw the contents in the computer readable form. ; One of the first steps in this direction is to recognize where the lines of the text are. Computational intelligence algorithms can be used to solve this problem. In the present paper, two groups of algorithms, namely, projection-based and tensor voting-based, are compared. The performance is evaluated on a data set and with the procedure proposed by the organizers of the ICDAR 2009 competition.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 30, number 3 (2020) ; kliknij tutaj, żeby przejść
Biblioteka Uniwersytetu Zielonogórskiego
17 lip 2025
17 lip 2025
14
https://zbc.uz.zgora.pl/repozytorium/publication/101250
| Nazwa wydania | Data |
|---|---|
| Line segmentation of handwritten text using histograms and tensor voting | 17 lip 2025 |
Ptak, Roman Żygadło, Bartosz Unold, Olgierd Korbicz, Józef (1951- ) - red. Uciński, Dariusz - red.