@inproceedings{2008-IUPR-06Jun_1627,
author = {Syed Saqib Bukhari and Faisal Shafait and Thomas M. Breuel},
title = {Segmentation of Curled Text Lines using Active Contours},
booktitle = {DAS},
year = {2008},
pdf = {2008-IUPR-06Jun_1627.pdf},
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__utma = {43439421.1215404805.1179231331.1212742371.1214560358.61},
__utmb = {43439421},
__utmc = {43439421},
abstract = {Segmentation of curled textlines from warped document
images is one of the major issues in document image de-
warping. Most of the curled textlines segmentation algo-
rithms present in the literature today are sensitive to the
degree of curl, direction of curl, and spacing between adja-
cent lines. We present a new algorithm for curled textline
segmentation which is robust to above mentioned problems
at the expense of high execution time. We will demon-
strate this insensitivity in a performance evaluation section.
Our approach is based on the state-of-the-art image seg-
mentation technique: Active Contour Model (Snake) with
the novel idea of several baby snakes and their conver-
gence in a vertical direction only. Experiment on publically
available CBDAR 2007 document image dewarping contest
dataset shows our textline segmentation algorithm accuracy
of 97.96%.},
category = {document image management}
}