A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
A Generic System for Form Dropout
IEEE Transactions on Pattern Analysis and Machine Intelligence
A protocol for performance evaluation of line detection algorithms
Machine Vision and Applications - Special issue on performance evaluation
INFORMys: A Flexible Invoice-Like Form-Reader System
IEEE Transactions on Pattern Analysis and Machine Intelligence
Description and recognition of form and automated form data entry
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Robust table-form structure analysis based on box-driven reasoning
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
Form Frame Line Detection with Directional Single-Connected Chain
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Efficient combination of the fuzzy hough transform and the burns segment detector
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
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In this paper we present a novel model based approach todetect severely broken parallel lines in noisy textual documents.It is important to detect and remove these lines so thetext can be segmented and recognized. We use DirectionalSingle-Connected Chain, a vectorization based algorithm,to extract the line segments. We then instantiate a parallelline model with three parameters: the skew angle, the verticalline gap, and the vertical translation. A coarse-to-fineapproach is used to improve the estimation accuracy. Fromthe model we can incorporate the high level contextual informationto enhance detection results even when lines areseverely broken. Our experimental results show our methodcan detect 94% of the lines in our database with 168 noisyArabic document images.