Table detection is a challenging problem and plays an important role in document layout
analysis. In this paper, we propose an effective method to identify the table region from …

Tables are an easy way to represent information in a structural form. Table recognition is
important for the extraction of such information from document images. Usually, modern …

Automatically detecting and parsing tables into an indexable and searchable format is an
important problem in document digitization. It relates to computer vision, machine learning …

Abstract Table Structure Recognition is an essential part of end-to-end tabular data
extraction in document images. The recent success of deep learning model architectures in …

In this paper, we propose two parameter-free table detection methods: one for the closed
tables and other for open tables. The unifying idea is multigaussian analysis. Multigaussian …

Nowadays, the field of multimedia retrieval system has earned a lot of attention as it helps
retrieve information more efficiently and accelerates daily tasks. Within this context, image …

Table detection is an essential step in many document analysis systems. Tabular data are a
pivotal form of information representation that can organize data in a conventional structure …

Perhaps, PDF is the most popular format to share non-editable documents. PDF documents
are often untagged. In particular, this means that positions and the cell structure of tables are …

In this paper, we propose a heuristics-based method for automatic detection and extraction
of tabular data from document images. The proposed approach utilizes page segmentation …

Densely-packed but structured scientific data are typically presented in the form of tables,
which often appear in raster image form. To interpret data from scanned tables …