DocumentCode :
2763446
Title :
Character grouping technique using 3D neighborhood graphs in raster map
Author :
Kang, Yong-Bin ; Ok, Se-Young ; Cho, Hwan-Gue
Author_Institution :
Poydong, Seoul, South Korea
Volume :
2
fYear :
1998
fDate :
16-20 Aug 1998
Firstpage :
1092
Abstract :
The main problem in this paper is how to find the character which is placed on a line or curves of raster map. We give one novel algorithm to group each separated characters in a map. This word grouping is difficult especially in a map, since a map has many different types of character and each word has its own slanting line. For this, we propose the 3D neighborhood graph G from a given set of characters. In this graph, each vertex of G represents the separated characters and it is placed in 3D space according to the size of the character. This makes the bigger characters being located in the upper position, the smaller characters being placed in the bottom. We give an edge if two vertices are nearly placed in that 3D space. By this edge connection strategy we can easily find the words of various different size in a map
Keywords :
character recognition; document image processing; edge detection; feature extraction; string matching; 3D neighborhood graphs; 3D space; character grouping; character recognition; document analysis; edge connection; feature extraction; raster map; text strings; word grouping; Application software; Computer graphics; Computer science; Feature extraction; Image analysis; Image recognition; Image segmentation; Natural languages; Read only memory; Text analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location :
Brisbane, Qld.
ISSN :
1051-4651
Print_ISBN :
0-8186-8512-3
Type :
conf
DOI :
10.1109/ICPR.1998.711883
Filename :
711883
Link To Document :
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