A Generic System for Form Dropout
IEEE Transactions on Pattern Analysis and Machine Intelligence
Line Removal and Restoration of Handwritten Characters on the Form Documents
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Speeding-up Chinese Character Recognition in an Automatic Document Reading System
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Segmentation of interference marks using morphological approach
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Strokes recovering from static handwriting
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
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Characters sometimes overlap with non-textual lines in form documents and these interfered-characters would generally be recognized with poor accuracy. In this paper, we propose a two-step interfering-line removing method. Positions and orientations of interfering-lines are first detected by the Hough transform. Interferingline widths are then determined from projection histograms. An ambiguous area is defined to bound an interfering-line. Black runs in the ambiguous are classified into four types and grouped into run-groups. The directions of hidden character strokes in each run-groups are predicted. Black pixels located in these hidden strokes are regarded as character pixels and the other black pixels are considered as interfering pixels, which will be removed then. Most OCR engines are trained by noninterfered sample characters. In order to recognize interfered-characters, we adjust the feature values by assigning a stability value to each of sub-regions. In our collected 1820 interfered handwritten Chinese characters, the recognition accuracy was 24.02% for interfered-characters and 89. 91 % for characters after removing interfering-lines.