A robust table registration method for batch table OCR processing

Abstract

A robust table registration method is proposed in this paper for a better understanding on structured information from scanned table images. Scanned images can be heavily degraded because of scanning effects, binarization or purely document itself. For batch processing images with the same table structure, normally the table model is provided and can be used to overcome most challenging quality factors. The given table model is used as the ground truth in this paper. However, only rough precision is needed on table cell dimensions and this makes providing the table model an easier task. The method was tested on Multilingual Automatic Document Classification Analysis and Translation (MADCAT) images and a promising performance is achieved.