Table Recognition and Understanding from PDF Files

Abstract

We propose a flexible method for detecting and understanding tables in PDF files, which is not reliant upon one particular feature being present, for example ruling lines or indentations, and is therefore applicable to a wide variety of visual presentations. We describe the steps required in transforming the low-level PDF instructions into text segments, lines and boxes on a page. We propose three different classifications for published tables, and develop methods to detect these tables and correctly identify their respective rows and columns. We also explain how to recognize spanning rows and columns, and multi-line rows. Experimental results show that our algorithm is effective in converting a wide variety of tabular presentations into HTML for information extraction purposes.