A new table interpretation methodology with little knowledge base: table interpretation methodology

Authors:
Luiz Antônio Pereira Neves;João Marques de Carvalho;Jacques Facon;Flávio Bortolozzi
Affiliations:
Universidade Federal, de Campina Grande, Brazil and Pontificia Universidade Católica do, Paraná, Brazil;Universidade Federal, de Campina Grande, Brazil;Universidade Católica do, Paraná, Brazil;Universidade Católica do, Paraná, Brazil
Venue:
Proceedings of the 2006 ACM symposium on Applied computing
Year:
2006

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Abstract

In this paper, a new methodology for table-form interpretation with little previous knowledge is presented. The first module performs the identification of line intersections in a table-form, the second module detects and corrects wrong intersections produced by fault intersection segments or by table artefacts (smudges, overlapping of handwritten data and fault segments). The third module performs the table-form cell extraction. The features used to interpret the table-form are directly extracted from the image itself by means of morphological tools. The evaluation of the efficiency is carried out from a total of 305 table-form images. Experiments showed significant and promising results. The proposed approach reached a success rate over than 87% on average. The main advantage of the proposed methodology is requiring little knowledge from documents, being able to apply for a table-form majority.