Automatic Table Detection and Retention from Scanned Document Images via Analysis of Structural Information

被引：0

作者：

Ranka, Varsha ^{[1
]}

Patil, Shubham ^{[1
]}

Patni, Shubham ^{[1
]}

Raut, Tushar ^{[1
]}

Mehrotra, Kapil ^{[2
]}

Gupta, Manish Kumar ^{[2
]}

机构：

[1] PICT, Dept Comp Engn, Pune, Maharashtra, India

[2] Ctr Dev Adv Comp, Pune, Maharashtra, India

来源：

2017 FOURTH INTERNATIONAL CONFERENCE ON IMAGE INFORMATION PROCESSING (ICIIP) | 2017年

关键词：

Optical Character Recognition; Table detection; Table Retention; Layout analysis; Document Analysis and Recognition;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The problem of automatic table detection has always been a great topic of debate in the field of Document Analysis and Recognition (DAR). Digital documents are efficient than their printed counterparts for storage, maintenance and republishing. Being a non-textual object of a document, tables prevent OCR system to digitize a document perfectly and distorts layout and structure of digitized documents. There is no available algorithm or method which solves this problem for all possible types of tables. This paper tackles the problem of table detection and retention by proposing a bi-modular approach based on structural information of tables. This structural information includes bounding lines, row/column separators and space between columns. Through analysis of these properties, our experiments on a dataset of above 600 images consisting of more than 829 tables have detected 90% of the table correctly.

引用

页码：244 / 249

页数：6

共 10 条

[1] Akmal Jahan M. A. C., 2014, 7th International Conference on Information and Automation for Sustainability (ICIAfS), P1, DOI 10.1109/ICIAFS.2014.7069552
[2] Bansal A., 2014, ICVGIP 14, V14
[3] Deivalakshmi S., 2014, 2014 International Conference on Communications and Signal Processing (ICCSP), P270, DOI 10.1109/ICCSP.2014.6949843
[4] Gatos B., 2005, AUTOMATIC TABLE DETE, P609
[5] Harit G., 2012, ICVGIP 12, V12
[6] Kasar T., 2013, INT C DOC AN REC ICD
[7] Table structure recognition based on robust block segmentation
Kieninger, TG
[J]. DOCUMENT RECOGNITION V, 1998, 3305 : 22 - 32
[8] Simple and effective table detection system from document images
Mandal, S.
Chowdhury, S. P.
Das, A. K.
Chanda, Bhabatosh
[J]. INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION, 2006, 8 (2-3) : 172 - 182
[9] Shafait F., 2010, P 9 IAPR INT WORKSH, P65
[10] Tian YY, 2014, 2014 2ND INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI), P818, DOI 10.1109/ICSAI.2014.7009397

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