A table-form extraction with artefact removal

We present a novel methodology for extracting the structure of handwritten filled table-forms. The method identifies the table-form line intersections, detecting and correcting wrong intersections produced by faulty line segments or by table artefacts. Examples of artefacts are overlapping data, broken segments, and smudges. A novel method for artefact identification and deletion is also proposed. The last step performs the extraction of table-form cells. A database of 350 table-form images was used for evaluation, showing that the artefact identification method improves the performance of the table-forms structure extractor. The proposed approach reached a success rate of 85%.