DocumentCode :
3075921
Title :
Vision knowledge vectorization: converting raster images into vector form
Author :
Jennings, C. ; Parker, J.R.
Author_Institution :
Dept. of Comput. Sci., Calgary Univ., Alta., Canada
Volume :
1
fYear :
1994
fDate :
9-13 Oct 1994
Firstpage :
311
Abstract :
The traditional erosion based vectorization methods create flawed vector representations, which must then be corrected by hand. Some of these flaws are due to artifacts injected by the thinning process, while others are intrinsic to the process-perfect vectorization is not, in general, possible. The approach described here is based on looking at the complete search space, reduced by using knowledge about the image domain-that of engineering diagrams. The search space is reduced far enough that very good line and curve extractions can be performed. The results are compared against traditional vectorization in terms of the time needed by a human to repair the resulting line drawings
Keywords :
document image processing; artifacts; curve extractions; engineering diagrams; line extractions; raster images; search space; thinning process; vision knowledge vectorization; Computer science; Computer vision; Data mining; Engineering drawings; Geographic Information Systems; Humans; Image converters; Knowledge engineering; Laboratories; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
Type :
conf
DOI :
10.1109/ICPR.1994.576286
Filename :
576286
Link To Document :
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