A Complete System for Detection and Identification of Tabular Structures from Document Images

Mandal, Sekhar; Chowdhury, Shyama Prosad; Das, Amit Kumar; Chanda, Bhabatosh

doi:10.1007/978-3-540-30126-4_27

“…It is based on certain simple-yet-effective structural properties without resorting to individual solutions for different entities. This approach was, to the best of our knowledge, first reported by the present authors in (Mandal, Chowdhury, Das, & Chanda, 2004) as a naive attempt to classify page entities on the basis of tabular and non-tabular text. The present work is an all-round improvement of our earlier scheme in several important aspects.…”

Section: Classification Of Tabular and Non-tabular Structuresmentioning

confidence: 97%

A Unified Algorithm for Identification of Various Tabular Structures from Document Images

Mandal

¹

,

Das

²

,

Bhowmick

³

et al. 2011

International Journal of Digital Library Systems

Self Cite

1

0

View full text Add to dashboard Cite

This paper presents a unified algorithm for segmentation and identification of various tabular structures from document page images. Such tabular structures include conventional tables and displayed math-zones, as well as Table of Contents (TOC) and Index pages. After analyzing the page composition, the algorithm initially classifies the input set of document pages into tabular and non-tabular pages. A tabular page contains at least one of the tabular structures, whereas a non-tabular page does not contain any. The approach is unified in the sense that it is able to identify all tabular structures from a tabular page, which leads to a considerable simplification of document image segmentation in a novel manner. Such unification also results in speeding up the segmentation process, because the existing methodologies produce time-consuming solutions for treating different tabular structures as separate physical entities. Distinguishing features of different kinds of tabular structures have been used in stages in order to ensure the simplicity and efficiency of the algorithm and demonstrated by exhaustive experimental results.

show abstract

Locating tables in scanned documents for reconstructing and republishing

Mohamed-Abdul-Cader

¹

,

Ragel

²

2014

7th International Conference on Information and Automation for Sustainability

View full text Add to dashboard Cite

Pool of knowledge available to the mankind depends on the source of learning resources, which can vary from ancient printed documents to present electronic material. The rapid conversion of material available in traditional libraries to digital form needs a significant amount of work if we are to maintain the format and the look of the electronic documents as same as their printed counterparts. Most of the printed documents contain not only characters and its formatting but also some associated non text objects such as tables, charts and graphical objects. It is challenging to detect them and to concentrate on the format preservation of the contents while reproducing them. To address this issue, we propose an algorithm using local thresholds for word space and line height to locate and extract all categories of tables from scanned document images. From the experiments performed on 298 documents, we conclude that our algorithm has an overall accuracy of about 75% in detecting tables from the scanned document images. Since the algorithm does not completely depend on rule lines, it can detect all categories of tables in a range of scanned documents with different font types, styles and sizes to extract their formatting features. Moreover, the algorithm can be applied to locate tables in multi column layouts with small modification in layout analysis. Treating tables with their existing formatting features will tremendously help the reproducing of printed documents for reprinting and updating purposes.

show abstract

A Unified Algorithm for Identification of Various Tabular Structures from Document Images

Mandal

¹

,

Das

²

,

Bhowmick

³

et al.

Modern Library Technologies for Data Storage, Retrieval, and Use

0

View full text Add to dashboard Cite

This paper presents a unified algorithm for segmentation and identification of various tabular structures from document page images. Such tabular structures include conventional tables and displayed math-zones, as well as Table of Contents (TOC) and Index pages. After analyzing the page composition, the algorithm initially classifies the input set of document pages into tabular and non-tabular pages. A tabular page contains at least one of the tabular structures, whereas a non-tabular page does not contain any. The approach is unified in the sense that it is able to identify all tabular structures from a tabular page, which leads to a considerable simplification of document image segmentation in a novel manner. Such unification also results in speeding up the segmentation process, because the existing methodologies produce time-consuming solutions for treating different tabular structures as separate physical entities. Distinguishing features of different kinds of tabular structures have been used in stages in order to ensure the simplicity and efficiency of the algorithm and demonstrated by exhaustive experimental results.

show abstract

A Complete System for Detection and Identification of Tabular Structures from Document Images

Cited by 3 publications

References 17 publications

A Unified Algorithm for Identification of Various Tabular Structures from Document Images

A Unified Algorithm for Identification of Various Tabular Structures from Document Images

Locating tables in scanned documents for reconstructing and republishing

A Unified Algorithm for Identification of Various Tabular Structures from Document Images

Contact Info

Product

Resources

About