Bibtex entry:

@inproceedings{iwfhr5:Ven,
   key = {iwfhr5:Ven},
   keywords = {ocr, segmentation, algorithms},
   author = {F. Venturelli and Zs. M. Kovacs-V.},
   title = {An Unconstrained Handwritten Line Segmentation Technique},
   booktitle = {Proc. of IWFHR5 Essex - England},
   month = {Sep},
   year = {1996},
   pages={385--388},
   abstract={
In this paper a line segmentation technique is presented. It can be
used for the extraction of handwritten lines from boxes or full
pages. There is no assumption on the character sizes, on the number of
lines or on the gap between lines. The methodology is based on a
pipeline architecture made of three stages. Each stage is composed of
a coarse line segmenter and a fine line follower to correctly separate
the intruding characters into adjacent lines.  The coarse line
segmenter is based on the idea of dividing each line into several
columns and on the use of local horizontal projection histograms. The
fine line follower uses character contour information. The three
stages employ slightly different methods to improve the overall
quality. The lack of writing size knowledge is overcome by iterating
the segmentation and detecting the error conditions. This line
segmentation technique has been applied to the "Constitution" boxes of
NIST SDB 1 and to the multi-line boxes of NIST SDB 11-13. The line
segmentation success is 99.72%, but all the remaining 0.28%
incorrectly processed images are detected and they may be signaled to
the outer document processing system.
},
}

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