Autor:

Babczyński, Tomasz ; Ptak, Roman

Współtwórca:

Kołodziej, Joanna - ed. ; Pllana, Sabri - ed. ; Vitabile , Salvatore - ed.

Tytuł:

Line segmentation of handwritten text using histograms and tensor voting

Podtytuł:

.

Tytuł publikacji grupowej:

AMCS, volume 30 (2020)

Temat i słowa kluczowe:

document image processing ; handwritten text line segmentation ; projection profile ; text string ; off-line cursive script recognition ; ICDAR 2009 competition

Abstract:

There are a large number of historical documents in libraries and other archives throughout the world.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.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2020

Typ zasobu:

artykuł

DOI:

10.34768/amcs-2020-0043

Strony:

585-596

Źródło:

AMCS, volume 30, number 3 (2020) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego